{ "cells": [ { "cell_type": "markdown", "metadata": { "id": "IqM-T1RTzY6C" }, "source": [ "To run this, press \"*Runtime*\" and press \"*Run all*\" on a **free** Tesla T4 Google Colab instance!\n", "
\n", "\n", "To install Unsloth on your own computer, follow the installation instructions on our Github page [here](https://github.com/unslothai/unsloth?tab=readme-ov-file#-installation-instructions).\n", "\n", "You will learn how to do [data prep](#Data), how to [train](#Train), how to [run the model](#Inference), & [how to save it](#Save) (eg for Llama.cpp).\n", "\n", "**[NEW] Try 2x faster inference in a free Colab for Llama-3.1 8b Instruct [here](https://colab.research.google.com/drive/1T-YBVfnphoVc8E2E854qF3jdia2Ll2W2?usp=sharing)**\n", "\n", "**[NEW] Finetuning Mistral Small 22b fits in a 16GB GPU!**" ] }, { "cell_type": "code", "execution_count": 1, "metadata": { "id": "2eSvM9zX_2d3" }, "outputs": [], "source": [ "%%capture\n", "!pip install unsloth\n", "# Also get the latest nightly Unsloth!\n", "!pip uninstall unsloth -y && pip install --upgrade --no-cache-dir \"unsloth[colab-new] @ git+https://github.com/unslothai/unsloth.git\"" ] }, { "cell_type": "markdown", "metadata": { "id": "r2v_X2fA0Df5" }, "source": [ "* We support Llama, Mistral, Phi-3, Gemma, Yi, DeepSeek, Qwen, TinyLlama, Vicuna, Open Hermes etc\n", "* We support 16bit LoRA or 4bit QLoRA. Both 2x faster.\n", "* `max_seq_length` can be set to anything, since we do automatic RoPE Scaling via [kaiokendev's](https://kaiokendev.github.io/til) method.\n", "* [**NEW**] We make Gemma-2 9b / 27b **2x faster**! See our [Gemma-2 9b notebook](https://colab.research.google.com/drive/1vIrqH5uYDQwsJ4-OO3DErvuv4pBgVwk4?usp=sharing)\n", "* [**NEW**] To finetune and auto export to Ollama, try our [Ollama notebook](https://colab.research.google.com/drive/1WZDi7APtQ9VsvOrQSSC5DDtxq159j8iZ?usp=sharing)\n", "* [**NEW**] We make Mistral NeMo 12B 2x faster and fit in under 12GB of VRAM! [Mistral NeMo notebook](https://colab.research.google.com/drive/17d3U-CAIwzmbDRqbZ9NnpHxCkmXB6LZ0?usp=sharing)" ] }, { "cell_type": "code", "execution_count": 2, "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 403, "referenced_widgets": [ "6a0264ad9e1045e9b276da5afea538e4", "6889ef6686684e8faee29a64986488ad", "28575a44bd4a4ff4995bef61a1ff923f", "ac2708c092394bdfbad40e65c5fcf5bd", "362a469d210a40c4beb44614d0dff94d", "3b208739190647aba89d38664f3c04ff", "13858c39f00043eab784b43e78f75e96", "be112d605e874960b57620ab725742c1", "71d2164bd80c4c7ebdba192b545307e0", "cfc8db4601c241f5aa1664a2df9ad0a2", "025890c6531d450b9ad67861cff5eb66", "974e02c218174ee3ac8f7097205dbea3", "b4c1a2579601463eae261e9d8d519658", "168b4bc0ddd548cc8e3632eee17f6333", "b79b90dfab6340b19cd27f40c497420d", "429d057b1f4b46b1a59deff19df8c51f", "ce48b32b9ad24145814ae20bfd91b56d", "9c4f0814b946400c8d35d973a8907f8a", "8657ee65ecd84d5a9060532e3120ebc2", "27c682c7ccd54f4e90597cbeff916f5b", "c5f5ed3035a54779ac1d2c5c7743ab6d", "730d88a3a02e4b528efd0b7a5b4bbe51", "c3f26313e34440e0918dc5e6c53fe256", "517365223084483a8d8b59410c6fe95a", "da6c2c2731cb4709a271bca5478a245d", "6dba4a23cf4547adb17eaf446eef7297", "67793453c68943329ccd77c0b5200f2a", "233836d2c7b048009a8d5f2039ff0483", "69fa12ed214d49df911ad7f7e4cf215b", "ef2bd43356e547c8b6813308b61eab04", "3c9e9bb23c054fc8b9f3a6658e8d5a40", "9c6d70b74f3d4c0c9fce7e8c379a4d2f", "538539b1e9134709b26ac83664b5b114", "f4334c21a9d24e48b43232cce101e395", "38b7d7231e3a4b078ff15c0af7d4bab6", "3f3b84e262d744558b132ac31da96081", "afb067fcfc1a4bc8aee1206e0e061100", "fad80247656042788748ea5c5c9f64df", "82c8aca0f1a24c38a2c111dfa85df233", "9dc305d92ded49e58e76469d67d9a2a7", "749165aa361b47eda47e778a37176012", "a4ff849ee64f4acd8296a24d2370a25b", "b064befe0f57430ab07d62c18ea1b8e3", "c5d1c7b31fe044f5b4882b29c0c6948b", "d02ed9830c494a59a67c1e95c2b684bd", "7e0bca45410b467c92f97deaaf153ce6", "16f2c1312876443784df678b0fe424b1", "1480812645954012a9dc22049f1295a5", "856c8aab5f8e451ebc7e19e79105ed0b", "4664916ffbe54f33adbf1b416fd5f384", "6f3bafec64374b68af5d6bc79774951d", "d75e04ea7c4644a3a3390b98284eb71e", "9f7cf13438a84bb29002d4dcf9583fd4", "7943696966dd4434900e30aed33fafda", "542a9b28ae904946a6fbbb57d1815e07", "d38ace4d6758421f8ac21b5317a90cda", "ab25c4681afc4516acd2daf62c2e526b", "fd706226b91847a39fc3dde16df4ce9d", "3f47030858274683b8b14ad06cc8c0d5", "252c63f990844e079f30f825d2c07184", "722ae7185340428ea42f1f0322d11811", "6e394dc9bb584d7b84885265267f2174", "677de59ed6a941eb980abac52eae5a69", "cec0767678744a81a457f9bfa2287e92", "c5e622547fb048128d67240d16152f79", "251591a1f67849b59664988d900c9320" ] }, "id": "QmUBVEnvCDJv", "outputId": "5253330d-8a3d-4826-ab64-87f2ef9f1aaa" }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "🦥 Unsloth: Will patch your computer to enable 2x faster free finetuning.\n", "==((====))== Unsloth 2024.10.7: Fast Mistral patching. Transformers = 4.44.2.\n", " \\\\ /| GPU: Tesla T4. Max memory: 14.748 GB. Platform = Linux.\n", "O^O/ \\_/ \\ Pytorch: 2.5.0+cu121. CUDA = 7.5. CUDA Toolkit = 12.1.\n", "\\ / Bfloat16 = FALSE. FA [Xformers = 0.0.28.post2. FA2 = False]\n", " \"-____-\" Free Apache license: http://github.com/unslothai/unsloth\n", "Unsloth: Fast downloading is enabled - ignore downloading bars which are red colored!\n" ] }, { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "6a0264ad9e1045e9b276da5afea538e4", "version_major": 2, "version_minor": 0 }, "text/plain": [ "model.safetensors: 0%| | 0.00/4.14G [00:00, ?B/s]" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "974e02c218174ee3ac8f7097205dbea3", "version_major": 2, "version_minor": 0 }, "text/plain": [ "generation_config.json: 0%| | 0.00/157 [00:00, ?B/s]" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "c3f26313e34440e0918dc5e6c53fe256", "version_major": 2, "version_minor": 0 }, "text/plain": [ "tokenizer_config.json: 0%| | 0.00/137k [00:00, ?B/s]" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "f4334c21a9d24e48b43232cce101e395", "version_major": 2, "version_minor": 0 }, "text/plain": [ "tokenizer.model: 0%| | 0.00/587k [00:00, ?B/s]" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "d02ed9830c494a59a67c1e95c2b684bd", "version_major": 2, "version_minor": 0 }, "text/plain": [ "special_tokens_map.json: 0%| | 0.00/446 [00:00, ?B/s]" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "d38ace4d6758421f8ac21b5317a90cda", "version_major": 2, "version_minor": 0 }, "text/plain": [ "tokenizer.json: 0%| | 0.00/1.96M [00:00, ?B/s]" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stderr", "output_type": "stream", "text": [ "Unsloth: We fixed a gradient accumulation bug, but it seems like you don't have the latest transformers version!\n", "Please update transformers, TRL and unsloth via:\n", "`pip install --upgrade --no-cache-dir unsloth git+https://github.com/huggingface/transformers.git git+https://github.com/huggingface/trl.git`\n" ] } ], "source": [ "from unsloth import FastLanguageModel\n", "import torch\n", "max_seq_length = 2048 # Choose any! We auto support RoPE Scaling internally!\n", "dtype = None # None for auto detection. Float16 for Tesla T4, V100, Bfloat16 for Ampere+\n", "load_in_4bit = True # Use 4bit quantization to reduce memory usage. Can be False.\n", "\n", "model, tokenizer = FastLanguageModel.from_pretrained(\n", " model_name = \"unsloth/mistral-7b-v0.3\",\n", " max_seq_length = max_seq_length,\n", " dtype = dtype,\n", " load_in_4bit = load_in_4bit,\n", " token = \"hf_\",\n", ")" ] }, { "cell_type": "markdown", "metadata": { "id": "SXd9bTZd1aaL" }, "source": [ "We now add LoRA adapters so we only need to update 1 to 10% of all parameters!" ] }, { "cell_type": "code", "execution_count": 3, "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "6bZsfBuZDeCL", "outputId": "ddadd655-8a1f-44ad-8da8-8bbac5f0d3d7" }, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "Unsloth 2024.10.7 patched 32 layers with 32 QKV layers, 32 O layers and 32 MLP layers.\n" ] } ], "source": [ "model = FastLanguageModel.get_peft_model(\n", " model,\n", " r = 16, # Choose any number > 0 ! Suggested 8, 16, 32, 64, 128\n", " target_modules = [\"q_proj\", \"k_proj\", \"v_proj\", \"o_proj\",\n", " \"gate_proj\", \"up_proj\", \"down_proj\",],\n", " lora_alpha = 16,\n", " lora_dropout = 0, # Supports any, but = 0 is optimized\n", " bias = \"none\", # Supports any, but = \"none\" is optimized\n", " # [NEW] \"unsloth\" uses 30% less VRAM, fits 2x larger batch sizes!\n", " use_gradient_checkpointing = \"unsloth\", # True or \"unsloth\" for very long context\n", " random_state = 3407,\n", " use_rslora = False, # We support rank stabilized LoRA\n", " loftq_config = None, # And LoftQ\n", ")" ] }, { "cell_type": "markdown", "metadata": { "id": "vITh0KVJ10qX" }, "source": [ "\n", "### Data Prep\n", "We now use the Alpaca dataset from [yahma](https://huggingface.co./datasets/yahma/alpaca-cleaned), which is a filtered version of 52K of the original [Alpaca dataset](https://crfm.stanford.edu/2023/03/13/alpaca.html). You can replace this code section with your own data prep.\n", "\n", "**[NOTE]** To train only on completions (ignoring the user's input) read TRL's docs [here](https://huggingface.co./docs/trl/sft_trainer#train-on-completions-only).\n", "\n", "**[NOTE]** Remember to add the **EOS_TOKEN** to the tokenized output!! Otherwise you'll get infinite generations!\n", "\n", "If you want to use the `mistral3` template for ShareGPT datasets, try our conversational [notebook](https://colab.research.google.com/drive/1XamvWYinY6FOSX9GLvnqSjjsNflxdhNc?usp=sharing).\n", "\n", "For text completions like novel writing, try this [notebook](https://colab.research.google.com/drive/1ef-tab5bhkvWmBOObepl1WgJvfvSzn5Q?usp=sharing)." ] }, { "cell_type": "code", "execution_count": 4, "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 177, "referenced_widgets": [ "cef6b12b6552416ba87bdecf578c190f", "02426c5157ef4c92b1f912a2078032d6", "86dc1f03a7384d7b926c83ba9ad67625", "cd7d8e06b17c458593aba91e9981acd5", "e4f0ba3f0d6a487db87859777110804f", "13ee10ac59fb4401adb269038138e1d6", "bff66c38b69e4641865a4cbb532f47c1", "25fc5fc784a44aa491b841f185ef374d", "b882d5d3ca8442aaa2ddef15e47e5b45", "7d7f3cdde6e7482580883140dd1ba3ee", "467cef144dbd4d99bb1f5111c8ca25fa", "f9e1cac85c4e43bfb5e87c2b07d2d082", "26cb5c9cb78349b2b4e3243752093cc4", "9ad7254e49c84949a63df3569a9f6a34", "e9461ce46eb3437e8181e7d87031e048", "f4cde1cee7034425a60ecad0b5c07dda", "f61217d62cf94257b6cc9673d8e6cab1", "e26f854045484cd7a78f4df5b2e2bdc5", "9fe9c71e86824b8ba7f6757fb961f769", "37aeacc4ed6349b096efc3513d027c53", "62e5a5dea5fe404fb6b54561b17dfed2", "eaca2be4971344d6b56dcf64c3a69a8e", "fde39522ee7e4cd8bf6c5c8e6d07d1c3", "e82aa85c090e40b199df04e9761c0867", "6869bd240f6a4c27b19fa101cc665001", "3cc5e854f9a2462fb4eac1b7bbc26ebb", "c45929291edb45db829d6bf4caeb3cc7", "0d91e0c88db442e9a5f74d66c75fe33a", "8e2ad3625e624f7ba3ade89be147652d", "58c7dee9928346aba7a1986e32a7a776", "2595d0c6016849d999725fe309b38414", "4a38b8f3bcd74aa6af1d2d143fc5c1d2", "5d69c9c0eb454c998628d042720175c2", "ee1700276c2c4f36a391c9c64606d5a6", "ac0d0682ad7b48c0859b1fd3fe38f9a3", "dcbe29b4ad914c36be45549a87712136", "4c00184bff2b4f61a8b2b0866948bab0", "31b710c446a04859bb1bc068b9c42bcc", "9ce97683d0d14b8682b88d297b05e1e8", "b2b5c455e3874760b0153297d85412fb", "406e55d150d54f9db3f324e487e3aae9", "d2176f04c91a4bc5ba031980c22e5b99", "e9755d20f6cb4674b0bc6adb6da5015d", "a1f1649939a64ae6980283dece79934b", "c70ca67cf8074d389200b28c96c41c86", "b37374a767fc41c2b9e354f7cb11a802", "b36d3d2d9604420f8798330b296b61ee", "7040bb77fe904a378382fb8f0bb3ac3f", "232edccc247f40afb3aaf4458a45c084", "04405d46d02d4d9d9cafcd1a47f18b19", "0301b3c2076c4e158e8f5af6ce74df77", "ad4fc982db814395b18baa756ea16bc7", "d2525b5577a6425f8c77d66c12c76cc1", "aba4df1d6c5b4fde90452a6d6241cb9f", "59cff3508e8b41a7a2923c19e0016ff4" ] }, "id": "LjY75GoYUCB8", "outputId": "55a6f704-a9f8-4fb9-a3b4-b54f9f33ec0c" }, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "cef6b12b6552416ba87bdecf578c190f", "version_major": 2, "version_minor": 0 }, "text/plain": [ "README.md: 0%| | 0.00/450 [00:00, ?B/s]" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "f9e1cac85c4e43bfb5e87c2b07d2d082", "version_major": 2, "version_minor": 0 }, "text/plain": [ "train-00000-of-00002.parquet: 0%| | 0.00/158M [00:00, ?B/s]" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "fde39522ee7e4cd8bf6c5c8e6d07d1c3", "version_major": 2, "version_minor": 0 }, "text/plain": [ "train-00001-of-00002.parquet: 0%| | 0.00/144M [00:00, ?B/s]" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "ee1700276c2c4f36a391c9c64606d5a6", "version_major": 2, "version_minor": 0 }, "text/plain": [ "Generating train split: 0%| | 0/172026 [00:00, ? examples/s]" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "c70ca67cf8074d389200b28c96c41c86", "version_major": 2, "version_minor": 0 }, "text/plain": [ "Map: 0%| | 0/172026 [00:00, ? examples/s]" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "alpaca_prompt = \"\"\"Below is an instruction that describes a task, paired with an input that provides further context. Write a response that appropriately completes the request.\n", "\n", "### Instruction:\n", "{}\n", "\n", "### Input:\n", "{}\n", "\n", "### Response:\n", "{}\"\"\"\n", "\n", "EOS_TOKEN = tokenizer.eos_token # Must add EOS_TOKEN\n", "def formatting_prompts_func(examples):\n", " instructions = examples[\"instruction\"]\n", " inputs = examples[\"input\"]\n", " outputs = examples[\"output\"]\n", " texts = []\n", " for instruction, input, output in zip(instructions, inputs, outputs):\n", " # Must add EOS_TOKEN, otherwise your generation will go on forever!\n", " text = alpaca_prompt.format(instruction, input, output) + EOS_TOKEN\n", " texts.append(text)\n", " return { \"text\" : texts, }\n", "pass\n", "\n", "from datasets import load_dataset\n", "dataset = load_dataset(\"BanglaLLM/bangla-alpaca-orca\", split = \"train\")\n", "dataset = dataset.map(formatting_prompts_func, batched = True,)" ] }, { "cell_type": "markdown", "metadata": { "id": "idAEIeSQ3xdS" }, "source": [ "\n", "### Train the model\n", "Now let's use Huggingface TRL's `SFTTrainer`! More docs here: [TRL SFT docs](https://huggingface.co./docs/trl/sft_trainer). We do 60 steps to speed things up, but you can set `num_train_epochs=1` for a full run, and turn off `max_steps=None`. We also support TRL's `DPOTrainer`!" ] }, { "cell_type": "code", "execution_count": 5, "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 66, "referenced_widgets": [ "5c15f734bd2c4caeb1d0682cdfb6053a", "e202f31c8f854fa19844b176bc2917c2", "17e3bbf2df974aa1b840e4511ed76afd", "758310411c2c4c7bb318d082ed1cecf1", "f73f729c27414608b106a61357ef1f9b", "f7c0f25f2e3b4b81bc8c7c65fa65ba65", "7bb43fd56e754302bbe77c083996fa97", "4562d6548a394508b6a86dd9fd2cb7ca", "8057d60eab0843d1bcb06ff794b911aa", "abf15b1dd4f548229fdec015657aed73", "1a4e9b55836f42cfbb36fc4f0a01252c" ] }, "id": "95_Nn-89DhsL", "outputId": "6b426a8c-dd7a-42b2-cc4b-df8b073d4117" }, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "5c15f734bd2c4caeb1d0682cdfb6053a", "version_major": 2, "version_minor": 0 }, "text/plain": [ "Map (num_proc=2): 0%| | 0/172026 [00:00, ? examples/s]" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stderr", "output_type": "stream", "text": [ "max_steps is given, it will override any value given in num_train_epochs\n" ] } ], "source": [ "from trl import SFTTrainer\n", "from transformers import TrainingArguments\n", "from unsloth import is_bfloat16_supported\n", "\n", "trainer = SFTTrainer(\n", " model = model,\n", " tokenizer = tokenizer,\n", " train_dataset = dataset,\n", " dataset_text_field = \"text\",\n", " max_seq_length = max_seq_length,\n", " dataset_num_proc = 2,\n", " packing = False, # Can make training 5x faster for short sequences.\n", " args = TrainingArguments(\n", " per_device_train_batch_size = 1,\n", " gradient_accumulation_steps = 4,\n", " warmup_steps = 5,\n", " # num_train_epochs = 1, # Set this for 1 full training run.\n", " max_steps = 60,\n", " learning_rate = 2e-4,\n", " fp16 = not is_bfloat16_supported(),\n", " bf16 = is_bfloat16_supported(),\n", " logging_steps = 1,\n", " optim = \"adamw_8bit\",\n", " weight_decay = 0.01,\n", " lr_scheduler_type = \"linear\",\n", " seed = 3407,\n", " output_dir = \"outputs\",\n", " report_to = \"none\", # Use this for WandB etc\n", " ),\n", ")" ] }, { "cell_type": "code", "execution_count": 6, "metadata": { "cellView": "form", "colab": { "base_uri": "https://localhost:8080/" }, "id": "2ejIt2xSNKKp", "outputId": "c8de0099-cd1b-429c-99fb-15812b532566" }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "GPU = Tesla T4. Max memory = 14.748 GB.\n", "4.52 GB of memory reserved.\n" ] } ], "source": [ "#@title Show current memory stats\n", "gpu_stats = torch.cuda.get_device_properties(0)\n", "start_gpu_memory = round(torch.cuda.max_memory_reserved() / 1024 / 1024 / 1024, 3)\n", "max_memory = round(gpu_stats.total_memory / 1024 / 1024 / 1024, 3)\n", "print(f\"GPU = {gpu_stats.name}. Max memory = {max_memory} GB.\")\n", "print(f\"{start_gpu_memory} GB of memory reserved.\")" ] }, { "cell_type": "code", "execution_count": 7, "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 1000 }, "id": "yqxqAZ7KJ4oL", "outputId": "b99f519d-76a5-4dac-da82-71bd0a982bf8" }, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "==((====))== Unsloth - 2x faster free finetuning | Num GPUs = 1\n", " \\\\ /| Num examples = 172,026 | Num Epochs = 1\n", "O^O/ \\_/ \\ Batch size per device = 1 | Gradient Accumulation steps = 4\n", "\\ / Total batch size = 4 | Total steps = 60\n", " \"-____-\" Number of trainable parameters = 41,943,040\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "**** Unsloth: Please use our fixed gradient_accumulation_steps by updating transformers, TRL and Unsloth!\n", "`pip install --upgrade --no-cache-dir unsloth git+https://github.com/huggingface/transformers.git git+https://github.com/huggingface/trl.git`\n" ] }, { "data": { "text/html": [ "\n", "Step | \n", "Training Loss | \n", "
---|---|
1 | \n", "1.254200 | \n", "
2 | \n", "1.113400 | \n", "
3 | \n", "1.247700 | \n", "
4 | \n", "0.995000 | \n", "
5 | \n", "1.063900 | \n", "
6 | \n", "1.108900 | \n", "
7 | \n", "1.127300 | \n", "
8 | \n", "1.058100 | \n", "
9 | \n", "0.949900 | \n", "
10 | \n", "0.822700 | \n", "
11 | \n", "0.750700 | \n", "
12 | \n", "0.564500 | \n", "
13 | \n", "0.995400 | \n", "
14 | \n", "0.566200 | \n", "
15 | \n", "0.878100 | \n", "
16 | \n", "0.841100 | \n", "
17 | \n", "0.926300 | \n", "
18 | \n", "0.582900 | \n", "
19 | \n", "0.830300 | \n", "
20 | \n", "0.451800 | \n", "
21 | \n", "1.021900 | \n", "
22 | \n", "0.686900 | \n", "
23 | \n", "0.516700 | \n", "
24 | \n", "0.861300 | \n", "
25 | \n", "0.764900 | \n", "
26 | \n", "0.914000 | \n", "
27 | \n", "0.852000 | \n", "
28 | \n", "0.910100 | \n", "
29 | \n", "0.798400 | \n", "
30 | \n", "0.697900 | \n", "
31 | \n", "0.631000 | \n", "
32 | \n", "0.627200 | \n", "
33 | \n", "0.635200 | \n", "
34 | \n", "0.933800 | \n", "
35 | \n", "0.969300 | \n", "
36 | \n", "0.789100 | \n", "
37 | \n", "0.644300 | \n", "
38 | \n", "0.782700 | \n", "
39 | \n", "0.639500 | \n", "
40 | \n", "0.746300 | \n", "
41 | \n", "0.684400 | \n", "
42 | \n", "0.687900 | \n", "
43 | \n", "0.653900 | \n", "
44 | \n", "0.881100 | \n", "
45 | \n", "0.877500 | \n", "
46 | \n", "0.951100 | \n", "
47 | \n", "0.539300 | \n", "
48 | \n", "0.860900 | \n", "
49 | \n", "0.706300 | \n", "
50 | \n", "0.602400 | \n", "
51 | \n", "0.819100 | \n", "
52 | \n", "0.816000 | \n", "
53 | \n", "0.401500 | \n", "
54 | \n", "0.552000 | \n", "
55 | \n", "0.665500 | \n", "
56 | \n", "0.772100 | \n", "
57 | \n", "0.542500 | \n", "
58 | \n", "0.864100 | \n", "
59 | \n", "0.588400 | \n", "
60 | \n", "0.682700 | \n", "
"
],
"text/plain": [
" Below is an instruction that describes a task, paired with an input that provides further context. Write a response that appropriately completes the request.\\n\\n### Instruction:\\nপ্যারিসের একটি বিখ্যাত লম্বা টাওয়ার কি?\\n\\n### Input:\\n\\n\\n### Response:\\nপ্যারিসের একটি বিখ্যাত লম্বা টাওয়ার হল একটি বিশ্ববিদ্যালয়ে']"
]
},
"execution_count": 9,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# alpaca_prompt = Copied from above\n",
"FastLanguageModel.for_inference(model) # Enable native 2x faster inference\n",
"inputs = tokenizer(\n",
"[\n",
" alpaca_prompt.format(\n",
" \"প্যারিসের একটি বিখ্যাত লম্বা টাওয়ার কি?\", # instruction\n",
" \"\", # input\n",
" \"\", # output - leave this blank for generation!\n",
" )\n",
"], return_tensors = \"pt\").to(\"cuda\")\n",
"\n",
"outputs = model.generate(**inputs, max_new_tokens = 64, use_cache = True)\n",
"tokenizer.batch_decode(outputs)"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "CrSvZObor0lY"
},
"source": [
" You can also use a `TextStreamer` for continuous inference - so you can see the generation token by token, instead of waiting the whole time!"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "e2pEuRb1r2Vg",
"outputId": "d2ec001d-f2c9-4b15-cf3c-8fe07dbf34ea"
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
" Below is an instruction that describes a task, paired with an input that provides further context. Write a response that appropriately completes the request.\n",
"\n",
"### Instruction:\n",
"ক্রমাগত ফিবোনাচি সিকোয়েন্স করবেন\n",
"\n",
"### Input:\n",
"1, 1, 2, 3, 5, 8\n",
"\n",
"### Response:\n",
"1, 1, 2, 3, 5, 8, 13, 21, 34, 55, 89, 144, 233, 377, 610, 987, 1597, 2584, 4181, 6765, 10946, 17711, 28657, 46368, 75025, 121393\n"
]
}
],
"source": [
"# alpaca_prompt = Copied from above\n",
"FastLanguageModel.for_inference(model) # Enable native 2x faster inference\n",
"inputs = tokenizer(\n",
"[\n",
" alpaca_prompt.format(\n",
" \"ক্রমাগত ফিবোনাচি সিকোয়েন্স করবেন\", # instruction\n",
" \"1, 1, 2, 3, 5, 8\", # input\n",
" \"\", # output - leave this blank for generation!\n",
" )\n",
"], return_tensors = \"pt\").to(\"cuda\")\n",
"\n",
"from transformers import TextStreamer\n",
"text_streamer = TextStreamer(tokenizer)\n",
"_ = model.generate(**inputs, streamer = text_streamer, max_new_tokens = 128)"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "uMuVrWbjAzhc"
},
"source": [
"\n",
"### Saving, loading finetuned models\n",
"To save the final model as LoRA adapters, either use Huggingface's `push_to_hub` for an online save or `save_pretrained` for a local save.\n",
"\n",
"**[NOTE]** This ONLY saves the LoRA adapters, and not the full model. To save to 16bit or GGUF, scroll down!"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 194,
"referenced_widgets": [
"b394d711ae9242c788265f24c9a5ee42",
"b416ab6b52f3458fac03d62c44ff70c3",
"a1b0289b4fb146a59b9a3cbf3d1960d0",
"17b0a9fada8c402f90f7ab8ac3f84006",
"0994869c36a4402fa6bb0391c28027e0",
"635701e66e4f44b39ee094f1e3953af9",
"f5537922d4e94925a118b4102e1b5db3",
"9fee45523ded45d99517e718e1229408",
"ab0f71e2ef9543a799d270221b181e81",
"af4415d6ed8e4f149cbe55ad78640a8e",
"30983f8961bf4d83aacb77139690ed63",
"25016ec6a1ff42f893105c6e2abcc587",
"812857d3b17b403f989b3686cd520c02",
"473bd6610c564b8c8ad7a4cfa842979d",
"52081839832a457982c1415013515c97",
"3e568bf542e34c269de58bf11fd360b7",
"1b5347ed1b584555b82fe2e064595c67",
"4db8741fb5334720b19a134b0686eaea",
"9e51e029a44145c4ab2572cf91841696",
"2fb10f28bb0a4ed498f37668d890daed",
"8185830cefd94ee9805e4d79e8a20370",
"268e472f9e5845fc895e167d0513aece",
"a597206990d34c50a27d7f818ec24648",
"7677cdddfa104dc9bdc352596fd57679",
"dfa8f1e30c524bd9904de846bcb471df",
"1703f1e2cede4393bdc5576aa28d8d26",
"5b28753db78b45e3a083839ed0d71f17",
"5259049306d74fa39e4184250a24c042",
"8c9fd310580848ca8cc29b9b1bedc034",
"d143438a3e574a78be2e052dc6dae33d",
"34172978ed324047b813e6c42f5d8930",
"3f88168116bf490297e5e8fa0cd31796",
"5ac8c654086747a6850b6462ccee2c35",
"f4087fc8d18c4b9f8edf648f812f4b40",
"0e8b4643c42a462d90cbddd169fbb17b",
"d6f1a54080fe47699cff262103aa3c5a",
"4f98983f315f498981f5aa4de015076e",
"9c3c23ca3aab4f72ba94c8dc769d8e92",
"bcfa0a1a0022496e850f1d44cac0532b",
"391cef2e49a74c94bf484fda4b413b2b",
"54205208826b40d28f6387784198101a",
"4fb5a1222abd43c885f6d4e38f80ccf2",
"bd47b355ee6b45b681d0a03162e0872e",
"b7b47d22e60b4f70bcab335bccc016f7",
"4abd679e38dc4be09425ce126264175e",
"a1d2719d076145d8a88e101a53937596",
"161c263284df4f68a4358e4452dbef3a",
"f288ceb6bc954b9cab4113f679266350",
"66996de2024046ff9801f1d36859098c",
"9827853eb4ff417387631c3bc95e5d49",
"db269406493e40ee9257aeb1d9256901",
"07f800e8119b48f8b51dff9f48397810",
"1eae97f1eef448a28334a0055482204e",
"b7183b3341c34670aacfd32ec049ac25",
"93538debadaf4cad9b3563ea1b7c7e74"
]
},
"id": "upcOlWe7A1vc",
"outputId": "aee8974c-a0ad-4a2a-bca6-aeebd1e5adcf"
},
"outputs": [
{
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "b394d711ae9242c788265f24c9a5ee42",
"version_major": 2,
"version_minor": 0
},
"text/plain": [
"README.md: 0%| | 0.00/588 [00:00, ?B/s]"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "25016ec6a1ff42f893105c6e2abcc587",
"version_major": 2,
"version_minor": 0
},
"text/plain": [
" 0%| | 0/1 [00:00, ?it/s]"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "a597206990d34c50a27d7f818ec24648",
"version_major": 2,
"version_minor": 0
},
"text/plain": [
"adapter_model.safetensors: 0%| | 0.00/168M [00:00, ?B/s]"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Saved model to https://huggingface.co./vaugheu/MistralBangla3v7b\n"
]
},
{
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "f4087fc8d18c4b9f8edf648f812f4b40",
"version_major": 2,
"version_minor": 0
},
"text/plain": [
" 0%| | 0/1 [00:00, ?it/s]"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "4abd679e38dc4be09425ce126264175e",
"version_major": 2,
"version_minor": 0
},
"text/plain": [
"tokenizer.model: 0%| | 0.00/587k [00:00, ?B/s]"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# model.save_pretrained(\"MistralBangla3v7b\") # Local saving\n",
"# tokenizer.save_pretrained(\"MistralBangla3v7b\")\n",
"model.push_to_hub(\"vaugheu/MistralBangla3v7b\", token = \"hf_\") # Online saving\n",
"tokenizer.push_to_hub(\"vaugheu/MistralBangla3v7b\", token = \"hf_\") # Online saving"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "AEEcJ4qfC7Lp"
},
"source": [
"Now if you want to load the LoRA adapters we just saved for inference, set `False` to `True`:"
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "MKX_XKs_BNZR",
"outputId": "1f5fcf69-6162-4697-c28b-0ff2e22d5f8e"
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
" Below is an instruction that describes a task, paired with an input that provides further context. Write a response that appropriately completes the request.\n",
"\n",
"### Instruction:\n",
"প্যারিসের একটি বিখ্যাত লম্বা টাওয়ার কি?\n",
"\n",
"### Input:\n",
"\n",
"\n",
"### Response:\n",
"প্যারিসের একটি বিখ্যাত লম্বা টাওয়ার হল একটি বিশ্ববিদ্যালয়ের সাথে সংযোগ করার জন্য ব্যবহৃত একটি বিশ্ববিদ্যালয়ের সাথে \n"
]
}
],
"source": [
"if False:\n",
" from unsloth import FastLanguageModel\n",
" model, tokenizer = FastLanguageModel.from_pretrained(\n",
" model_name = \"MistralBangla3v7b\", # YOUR MODEL YOU USED FOR TRAINING\n",
" max_seq_length = max_seq_length,\n",
" dtype = dtype,\n",
" load_in_4bit = load_in_4bit,\n",
" )\n",
" FastLanguageModel.for_inference(model) # Enable native 2x faster inference\n",
"\n",
"# alpaca_prompt = You MUST copy from above!\n",
"\n",
"inputs = tokenizer(\n",
"[\n",
" alpaca_prompt.format(\n",
" \"প্যারিসের একটি বিখ্যাত লম্বা টাওয়ার কি?\", # instruction\n",
" \"\", # input\n",
" \"\", # output - leave this blank for generation!\n",
" )\n",
"], return_tensors = \"pt\").to(\"cuda\")\n",
"\n",
"from transformers import TextStreamer\n",
"text_streamer = TextStreamer(tokenizer)\n",
"_ = model.generate(**inputs, streamer = text_streamer, max_new_tokens = 128)"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "QQMjaNrjsU5_"
},
"source": [
"You can also use Hugging Face's `AutoModelForPeftCausalLM`. Only use this if you do not have `unsloth` installed. It can be hopelessly slow, since `4bit` model downloading is not supported, and Unsloth's **inference is 2x faster**."
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {
"id": "yFfaXG0WsQuE"
},
"outputs": [],
"source": [
"if False:\n",
" # I highly do NOT suggest - use Unsloth if possible\n",
" from peft import AutoPeftModelForCausalLM\n",
" from transformers import AutoTokenizer\n",
" model = AutoPeftModelForCausalLM.from_pretrained(\n",
" \"MistralBangla3v7b\", # YOUR MODEL YOU USED FOR TRAINING\n",
" load_in_4bit = load_in_4bit,\n",
" )\n",
" tokenizer = AutoTokenizer.from_pretrained(\"MistralBangla3v7b\")"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "f422JgM9sdVT"
},
"source": [
"### Saving to float16 for VLLM\n",
"\n",
"We also support saving to `float16` directly. Select `merged_16bit` for float16 or `merged_4bit` for int4. We also allow `lora` adapters as a fallback. Use `push_to_hub_merged` to upload to your Hugging Face account! You can go to https://huggingface.co./settings/tokens for your personal tokens."
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {
"id": "iHjt_SMYsd3P"
},
"outputs": [],
"source": [
"# Merge to 16bit\n",
"if False: model.save_pretrained_merged(\"model\", tokenizer, save_method = \"merged_16bit\",)\n",
"if False: model.push_to_hub_merged(\"vaugheu/MistralBangla3v7b\", tokenizer, save_method = \"merged_16bit\", token = \"\")\n",
"\n",
"# Merge to 4bit\n",
"if False: model.save_pretrained_merged(\"model\", tokenizer, save_method = \"merged_4bit\",)\n",
"if False: model.push_to_hub_merged(\"vaugheu/MistralBangla3v7b\", tokenizer, save_method = \"merged_4bit\", token = \"\")\n",
"\n",
"# Just LoRA adapters\n",
"if False: model.save_pretrained_merged(\"model\", tokenizer, save_method = \"lora\",)\n",
"if False: model.push_to_hub_merged(\"vaugheu/MistralBangla3v7b\", tokenizer, save_method = \"lora\", token = \"\")"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "TCv4vXHd61i7"
},
"source": [
"### GGUF / llama.cpp Conversion\n",
"To save to `GGUF` / `llama.cpp`, we support it natively now! We clone `llama.cpp` and we default save it to `q8_0`. We allow all methods like `q4_k_m`. Use `save_pretrained_gguf` for local saving and `push_to_hub_gguf` for uploading to HF.\n",
"\n",
"Some supported quant methods (full list on our [Wiki page](https://github.com/unslothai/unsloth/wiki#gguf-quantization-options)):\n",
"* `q8_0` - Fast conversion. High resource use, but generally acceptable.\n",
"* `q4_k_m` - Recommended. Uses Q6_K for half of the attention.wv and feed_forward.w2 tensors, else Q4_K.\n",
"* `q5_k_m` - Recommended. Uses Q6_K for half of the attention.wv and feed_forward.w2 tensors, else Q5_K.\n",
"\n",
"[**NEW**] To finetune and auto export to Ollama, try our [Ollama notebook](https://colab.research.google.com/drive/1WZDi7APtQ9VsvOrQSSC5DDtxq159j8iZ?usp=sharing)"
]
},
{
"cell_type": "code",
"execution_count": 15,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 1000,
"referenced_widgets": [
"9b1d1d58b37f4c0d8d43cd0bfe013238",
"59fab15e1c644925b04e051a02b42fa6",
"48aeec0877b54f7bab9cdb19e5792d6b",
"f751fcf5656b4240a576a0f4f309c51f",
"a73546aa20c54fc6aa8e414ebd91a336",
"7f35ec8e33ad453e905b9cad7a8cc2e5",
"c9a42afb532542c78e86ff4618406c47",
"843bc72177104b4782b95cb2f741129a",
"e13f629d29b0413985598507411192a3",
"528b64da057d43c395ff2ce1147a8576",
"6894219580074769999b672cb6e677cd",
"6ded895c12da47c89d0238e8ee66d11a",
"4962b782c5ca4670af98825a3438ac13",
"cde99f9f0c26432fbf9c34ee12f04852",
"2db4c72d8b2448ffad721123c1641cc7",
"9a33b54ab97449aa90aa43c3a017a419",
"79d52fabb462442a97f443c6b361f213",
"bc13c65b38ed4653ab3f9a99d861f4dc",
"9eeec3eb1b384a51b606d71e8ad9a171",
"ba699d43cb8f431b92a45858f6f0f6a5",
"fe84cb01a2fc4803b6959f18b194c476",
"c8509c42f414476e8ff36ca377a9b062"
]
},
"id": "FqfebeAdT073",
"outputId": "ae80596c-250b-4d21-ce8d-3acc4c0a0f68"
},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"Unsloth: You have 1 CPUs. Using `safe_serialization` is 10x slower.\n",
"We shall switch to Pytorch saving, which will take 3 minutes and not 30 minutes.\n",
"To force `safe_serialization`, set it to `None` instead.\n",
"Unsloth: Kaggle/Colab has limited disk space. We need to delete the downloaded\n",
"model which will save 4-16GB of disk space, allowing you to save on Kaggle/Colab.\n",
"Unsloth: Will remove a cached repo with size 4.1G\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Unsloth: Merging 4bit and LoRA weights to 16bit...\n",
"Unsloth: Will use up to 5.77 out of 12.67 RAM for saving.\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
" 53%|█████▎ | 17/32 [00:02<00:01, 10.91it/s]We will save to Disk and not RAM now.\n",
"100%|██████████| 32/32 [01:45<00:00, 3.31s/it]\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Unsloth: Saving tokenizer... Done.\n",
"Unsloth: Saving model... This might take 5 minutes for Llama-7b...\n",
"Unsloth: Saving model/pytorch_model-00001-of-00003.bin...\n",
"Unsloth: Saving model/pytorch_model-00002-of-00003.bin...\n",
"Unsloth: Saving model/pytorch_model-00003-of-00003.bin...\n",
"Done.\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"Unsloth: Converting mistral model. Can use fast conversion = True.\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"==((====))== Unsloth: Conversion from QLoRA to GGUF information\n",
" \\\\ /| [0] Installing llama.cpp will take 3 minutes.\n",
"O^O/ \\_/ \\ [1] Converting HF to GGUF 16bits will take 3 minutes.\n",
"\\ / [2] Converting GGUF 16bits to ['q8_0'] will take 10 minutes each.\n",
" \"-____-\" In total, you will have to wait at least 16 minutes.\n",
"\n",
"Unsloth: [0] Installing llama.cpp. This will take 3 minutes...\n",
"Unsloth: [1] Converting model at model into q8_0 GGUF format.\n",
"The output location will be /content/model/unsloth.Q8_0.gguf\n",
"This will take 3 minutes...\n",
"INFO:hf-to-gguf:Loading model: model\n",
"INFO:gguf.gguf_writer:gguf: This GGUF file is for Little Endian only\n",
"INFO:hf-to-gguf:Exporting model...\n",
"INFO:hf-to-gguf:gguf: loading model weight map from 'pytorch_model.bin.index.json'\n",
"INFO:hf-to-gguf:gguf: loading model part 'pytorch_model-00001-of-00003.bin'\n",
"INFO:hf-to-gguf:token_embd.weight, torch.float16 --> Q8_0, shape = {4096, 32768}\n",
"INFO:hf-to-gguf:blk.0.attn_q.weight, torch.float16 --> Q8_0, shape = {4096, 4096}\n",
"INFO:hf-to-gguf:blk.0.attn_k.weight, torch.float16 --> Q8_0, shape = {4096, 1024}\n",
"INFO:hf-to-gguf:blk.0.attn_v.weight, torch.float16 --> Q8_0, shape = {4096, 1024}\n",
"INFO:hf-to-gguf:blk.0.attn_output.weight, torch.float16 --> Q8_0, shape = {4096, 4096}\n",
"INFO:hf-to-gguf:blk.0.ffn_gate.weight, torch.float16 --> Q8_0, shape = {4096, 14336}\n",
"INFO:hf-to-gguf:blk.0.ffn_up.weight, torch.float16 --> Q8_0, shape = {4096, 14336}\n",
"INFO:hf-to-gguf:blk.0.ffn_down.weight, torch.float16 --> Q8_0, shape = {14336, 4096}\n",
"INFO:hf-to-gguf:blk.0.attn_norm.weight, torch.float16 --> F32, shape = {4096}\n",
"INFO:hf-to-gguf:blk.0.ffn_norm.weight, torch.float16 --> F32, shape = {4096}\n",
"INFO:hf-to-gguf:blk.1.attn_q.weight, torch.float16 --> Q8_0, shape = {4096, 4096}\n",
"INFO:hf-to-gguf:blk.1.attn_k.weight, torch.float16 --> Q8_0, shape = {4096, 1024}\n",
"INFO:hf-to-gguf:blk.1.attn_v.weight, torch.float16 --> Q8_0, shape = {4096, 1024}\n",
"INFO:hf-to-gguf:blk.1.attn_output.weight, torch.float16 --> Q8_0, shape = {4096, 4096}\n",
"INFO:hf-to-gguf:blk.1.ffn_gate.weight, torch.float16 --> Q8_0, shape = {4096, 14336}\n",
"INFO:hf-to-gguf:blk.1.ffn_up.weight, torch.float16 --> Q8_0, shape = {4096, 14336}\n",
"INFO:hf-to-gguf:blk.1.ffn_down.weight, torch.float16 --> Q8_0, shape = {14336, 4096}\n",
"INFO:hf-to-gguf:blk.1.attn_norm.weight, torch.float16 --> F32, shape = {4096}\n",
"INFO:hf-to-gguf:blk.1.ffn_norm.weight, torch.float16 --> F32, shape = {4096}\n",
"INFO:hf-to-gguf:blk.2.attn_q.weight, torch.float16 --> Q8_0, shape = {4096, 4096}\n",
"INFO:hf-to-gguf:blk.2.attn_k.weight, torch.float16 --> Q8_0, shape = {4096, 1024}\n",
"INFO:hf-to-gguf:blk.2.attn_v.weight, torch.float16 --> Q8_0, shape = {4096, 1024}\n",
"INFO:hf-to-gguf:blk.2.attn_output.weight, torch.float16 --> Q8_0, shape = {4096, 4096}\n",
"INFO:hf-to-gguf:blk.2.ffn_gate.weight, torch.float16 --> Q8_0, shape = {4096, 14336}\n",
"INFO:hf-to-gguf:blk.2.ffn_up.weight, torch.float16 --> Q8_0, shape = {4096, 14336}\n",
"INFO:hf-to-gguf:blk.2.ffn_down.weight, torch.float16 --> Q8_0, shape = {14336, 4096}\n",
"INFO:hf-to-gguf:blk.2.attn_norm.weight, torch.float16 --> F32, shape = {4096}\n",
"INFO:hf-to-gguf:blk.2.ffn_norm.weight, torch.float16 --> F32, shape = {4096}\n",
"INFO:hf-to-gguf:blk.3.attn_q.weight, torch.float16 --> Q8_0, shape = {4096, 4096}\n",
"INFO:hf-to-gguf:blk.3.attn_k.weight, torch.float16 --> Q8_0, shape = {4096, 1024}\n",
"INFO:hf-to-gguf:blk.3.attn_v.weight, torch.float16 --> Q8_0, shape = {4096, 1024}\n",
"INFO:hf-to-gguf:blk.3.attn_output.weight, torch.float16 --> Q8_0, shape = {4096, 4096}\n",
"INFO:hf-to-gguf:blk.3.ffn_gate.weight, torch.float16 --> Q8_0, shape = {4096, 14336}\n",
"INFO:hf-to-gguf:blk.3.ffn_up.weight, torch.float16 --> Q8_0, shape = {4096, 14336}\n",
"INFO:hf-to-gguf:blk.3.ffn_down.weight, torch.float16 --> Q8_0, shape = {14336, 4096}\n",
"INFO:hf-to-gguf:blk.3.attn_norm.weight, torch.float16 --> F32, shape = {4096}\n",
"INFO:hf-to-gguf:blk.3.ffn_norm.weight, torch.float16 --> F32, shape = {4096}\n",
"INFO:hf-to-gguf:blk.4.attn_q.weight, torch.float16 --> Q8_0, shape = {4096, 4096}\n",
"INFO:hf-to-gguf:blk.4.attn_k.weight, torch.float16 --> Q8_0, shape = {4096, 1024}\n",
"INFO:hf-to-gguf:blk.4.attn_v.weight, torch.float16 --> Q8_0, shape = {4096, 1024}\n",
"INFO:hf-to-gguf:blk.4.attn_output.weight, torch.float16 --> Q8_0, shape = {4096, 4096}\n",
"INFO:hf-to-gguf:blk.4.ffn_gate.weight, torch.float16 --> Q8_0, shape = {4096, 14336}\n",
"INFO:hf-to-gguf:blk.4.ffn_up.weight, torch.float16 --> Q8_0, shape = {4096, 14336}\n",
"INFO:hf-to-gguf:blk.4.ffn_down.weight, torch.float16 --> Q8_0, shape = {14336, 4096}\n",
"INFO:hf-to-gguf:blk.4.attn_norm.weight, torch.float16 --> F32, shape = {4096}\n",
"INFO:hf-to-gguf:blk.4.ffn_norm.weight, torch.float16 --> F32, shape = {4096}\n",
"INFO:hf-to-gguf:blk.5.attn_q.weight, torch.float16 --> Q8_0, shape = {4096, 4096}\n",
"INFO:hf-to-gguf:blk.5.attn_k.weight, torch.float16 --> Q8_0, shape = {4096, 1024}\n",
"INFO:hf-to-gguf:blk.5.attn_v.weight, torch.float16 --> Q8_0, shape = {4096, 1024}\n",
"INFO:hf-to-gguf:blk.5.attn_output.weight, torch.float16 --> Q8_0, shape = {4096, 4096}\n",
"INFO:hf-to-gguf:blk.5.ffn_gate.weight, torch.float16 --> Q8_0, shape = {4096, 14336}\n",
"INFO:hf-to-gguf:blk.5.ffn_up.weight, torch.float16 --> Q8_0, shape = {4096, 14336}\n",
"INFO:hf-to-gguf:blk.5.ffn_down.weight, torch.float16 --> Q8_0, shape = {14336, 4096}\n",
"INFO:hf-to-gguf:blk.5.attn_norm.weight, torch.float16 --> F32, shape = {4096}\n",
"INFO:hf-to-gguf:blk.5.ffn_norm.weight, torch.float16 --> F32, shape = {4096}\n",
"INFO:hf-to-gguf:blk.6.attn_q.weight, torch.float16 --> Q8_0, shape = {4096, 4096}\n",
"INFO:hf-to-gguf:blk.6.attn_k.weight, torch.float16 --> Q8_0, shape = {4096, 1024}\n",
"INFO:hf-to-gguf:blk.6.attn_v.weight, torch.float16 --> Q8_0, shape = {4096, 1024}\n",
"INFO:hf-to-gguf:blk.6.attn_output.weight, torch.float16 --> Q8_0, shape = {4096, 4096}\n",
"INFO:hf-to-gguf:blk.6.ffn_gate.weight, torch.float16 --> Q8_0, shape = {4096, 14336}\n",
"INFO:hf-to-gguf:blk.6.ffn_up.weight, torch.float16 --> Q8_0, shape = {4096, 14336}\n",
"INFO:hf-to-gguf:blk.6.ffn_down.weight, torch.float16 --> Q8_0, shape = {14336, 4096}\n",
"INFO:hf-to-gguf:blk.6.attn_norm.weight, torch.float16 --> F32, shape = {4096}\n",
"INFO:hf-to-gguf:blk.6.ffn_norm.weight, torch.float16 --> F32, shape = {4096}\n",
"INFO:hf-to-gguf:blk.7.attn_q.weight, torch.float16 --> Q8_0, shape = {4096, 4096}\n",
"INFO:hf-to-gguf:blk.7.attn_k.weight, torch.float16 --> Q8_0, shape = {4096, 1024}\n",
"INFO:hf-to-gguf:blk.7.attn_v.weight, torch.float16 --> Q8_0, shape = {4096, 1024}\n",
"INFO:hf-to-gguf:blk.7.attn_output.weight, torch.float16 --> Q8_0, shape = {4096, 4096}\n",
"INFO:hf-to-gguf:blk.7.ffn_gate.weight, torch.float16 --> Q8_0, shape = {4096, 14336}\n",
"INFO:hf-to-gguf:blk.7.ffn_up.weight, torch.float16 --> Q8_0, shape = {4096, 14336}\n",
"INFO:hf-to-gguf:blk.7.ffn_down.weight, torch.float16 --> Q8_0, shape = {14336, 4096}\n",
"INFO:hf-to-gguf:blk.7.attn_norm.weight, torch.float16 --> F32, shape = {4096}\n",
"INFO:hf-to-gguf:blk.7.ffn_norm.weight, torch.float16 --> F32, shape = {4096}\n",
"INFO:hf-to-gguf:blk.8.attn_q.weight, torch.float16 --> Q8_0, shape = {4096, 4096}\n",
"INFO:hf-to-gguf:blk.8.attn_k.weight, torch.float16 --> Q8_0, shape = {4096, 1024}\n",
"INFO:hf-to-gguf:blk.8.attn_v.weight, torch.float16 --> Q8_0, shape = {4096, 1024}\n",
"INFO:hf-to-gguf:blk.8.attn_output.weight, torch.float16 --> Q8_0, shape = {4096, 4096}\n",
"INFO:hf-to-gguf:blk.8.ffn_gate.weight, torch.float16 --> Q8_0, shape = {4096, 14336}\n",
"INFO:hf-to-gguf:blk.8.ffn_up.weight, torch.float16 --> Q8_0, shape = {4096, 14336}\n",
"INFO:hf-to-gguf:blk.8.ffn_down.weight, torch.float16 --> Q8_0, shape = {14336, 4096}\n",
"INFO:hf-to-gguf:blk.8.attn_norm.weight, torch.float16 --> F32, shape = {4096}\n",
"INFO:hf-to-gguf:blk.8.ffn_norm.weight, torch.float16 --> F32, shape = {4096}\n",
"INFO:hf-to-gguf:blk.9.attn_q.weight, torch.float16 --> Q8_0, shape = {4096, 4096}\n",
"INFO:hf-to-gguf:blk.9.attn_k.weight, torch.float16 --> Q8_0, shape = {4096, 1024}\n",
"INFO:hf-to-gguf:blk.9.attn_v.weight, torch.float16 --> Q8_0, shape = {4096, 1024}\n",
"INFO:hf-to-gguf:blk.9.attn_output.weight, torch.float16 --> Q8_0, shape = {4096, 4096}\n",
"INFO:hf-to-gguf:blk.9.ffn_gate.weight, torch.float16 --> Q8_0, shape = {4096, 14336}\n",
"INFO:hf-to-gguf:blk.9.ffn_up.weight, torch.float16 --> Q8_0, shape = {4096, 14336}\n",
"INFO:hf-to-gguf:blk.9.ffn_down.weight, torch.float16 --> Q8_0, shape = {14336, 4096}\n",
"INFO:hf-to-gguf:blk.9.attn_norm.weight, torch.float16 --> F32, shape = {4096}\n",
"INFO:hf-to-gguf:blk.9.ffn_norm.weight, torch.float16 --> F32, shape = {4096}\n",
"INFO:hf-to-gguf:blk.10.attn_q.weight, torch.float16 --> Q8_0, shape = {4096, 4096}\n",
"INFO:hf-to-gguf:blk.10.attn_k.weight, torch.float16 --> Q8_0, shape = {4096, 1024}\n",
"INFO:hf-to-gguf:blk.10.attn_v.weight, torch.float16 --> Q8_0, shape = {4096, 1024}\n",
"INFO:hf-to-gguf:blk.10.attn_output.weight, torch.float16 --> Q8_0, shape = {4096, 4096}\n",
"INFO:hf-to-gguf:blk.10.ffn_gate.weight, torch.float16 --> Q8_0, shape = {4096, 14336}\n",
"INFO:hf-to-gguf:blk.10.ffn_up.weight, torch.float16 --> Q8_0, shape = {4096, 14336}\n",
"INFO:hf-to-gguf:gguf: loading model part 'pytorch_model-00002-of-00003.bin'\n",
"INFO:hf-to-gguf:blk.10.ffn_down.weight, torch.float16 --> Q8_0, shape = {14336, 4096}\n",
"INFO:hf-to-gguf:blk.10.attn_norm.weight, torch.float16 --> F32, shape = {4096}\n",
"INFO:hf-to-gguf:blk.10.ffn_norm.weight, torch.float16 --> F32, shape = {4096}\n",
"INFO:hf-to-gguf:blk.11.attn_q.weight, torch.float16 --> Q8_0, shape = {4096, 4096}\n",
"INFO:hf-to-gguf:blk.11.attn_k.weight, torch.float16 --> Q8_0, shape = {4096, 1024}\n",
"INFO:hf-to-gguf:blk.11.attn_v.weight, torch.float16 --> Q8_0, shape = {4096, 1024}\n",
"INFO:hf-to-gguf:blk.11.attn_output.weight, torch.float16 --> Q8_0, shape = {4096, 4096}\n",
"INFO:hf-to-gguf:blk.11.ffn_gate.weight, torch.float16 --> Q8_0, shape = {4096, 14336}\n",
"INFO:hf-to-gguf:blk.11.ffn_up.weight, torch.float16 --> Q8_0, shape = {4096, 14336}\n",
"INFO:hf-to-gguf:blk.11.ffn_down.weight, torch.float16 --> Q8_0, shape = {14336, 4096}\n",
"INFO:hf-to-gguf:blk.11.attn_norm.weight, torch.float16 --> F32, shape = {4096}\n",
"INFO:hf-to-gguf:blk.11.ffn_norm.weight, torch.float16 --> F32, shape = {4096}\n",
"INFO:hf-to-gguf:blk.12.attn_q.weight, torch.float16 --> Q8_0, shape = {4096, 4096}\n",
"INFO:hf-to-gguf:blk.12.attn_k.weight, torch.float16 --> Q8_0, shape = {4096, 1024}\n",
"INFO:hf-to-gguf:blk.12.attn_v.weight, torch.float16 --> Q8_0, shape = {4096, 1024}\n",
"INFO:hf-to-gguf:blk.12.attn_output.weight, torch.float16 --> Q8_0, shape = {4096, 4096}\n",
"INFO:hf-to-gguf:blk.12.ffn_gate.weight, torch.float16 --> Q8_0, shape = {4096, 14336}\n",
"INFO:hf-to-gguf:blk.12.ffn_up.weight, torch.float16 --> Q8_0, shape = {4096, 14336}\n",
"INFO:hf-to-gguf:blk.12.ffn_down.weight, torch.float16 --> Q8_0, shape = {14336, 4096}\n",
"INFO:hf-to-gguf:blk.12.attn_norm.weight, torch.float16 --> F32, shape = {4096}\n",
"INFO:hf-to-gguf:blk.12.ffn_norm.weight, torch.float16 --> F32, shape = {4096}\n",
"INFO:hf-to-gguf:blk.13.attn_q.weight, torch.float16 --> Q8_0, shape = {4096, 4096}\n",
"INFO:hf-to-gguf:blk.13.attn_k.weight, torch.float16 --> Q8_0, shape = {4096, 1024}\n",
"INFO:hf-to-gguf:blk.13.attn_v.weight, torch.float16 --> Q8_0, shape = {4096, 1024}\n",
"INFO:hf-to-gguf:blk.13.attn_output.weight, torch.float16 --> Q8_0, shape = {4096, 4096}\n",
"INFO:hf-to-gguf:blk.13.ffn_gate.weight, torch.float16 --> Q8_0, shape = {4096, 14336}\n",
"INFO:hf-to-gguf:blk.13.ffn_up.weight, torch.float16 --> Q8_0, shape = {4096, 14336}\n",
"INFO:hf-to-gguf:blk.13.ffn_down.weight, torch.float16 --> Q8_0, shape = {14336, 4096}\n",
"INFO:hf-to-gguf:blk.13.attn_norm.weight, torch.float16 --> F32, shape = {4096}\n",
"INFO:hf-to-gguf:blk.13.ffn_norm.weight, torch.float16 --> F32, shape = {4096}\n",
"INFO:hf-to-gguf:blk.14.attn_q.weight, torch.float16 --> Q8_0, shape = {4096, 4096}\n",
"INFO:hf-to-gguf:blk.14.attn_k.weight, torch.float16 --> Q8_0, shape = {4096, 1024}\n",
"INFO:hf-to-gguf:blk.14.attn_v.weight, torch.float16 --> Q8_0, shape = {4096, 1024}\n",
"INFO:hf-to-gguf:blk.14.attn_output.weight, torch.float16 --> Q8_0, shape = {4096, 4096}\n",
"INFO:hf-to-gguf:blk.14.ffn_gate.weight, torch.float16 --> Q8_0, shape = {4096, 14336}\n",
"INFO:hf-to-gguf:blk.14.ffn_up.weight, torch.float16 --> Q8_0, shape = {4096, 14336}\n",
"INFO:hf-to-gguf:blk.14.ffn_down.weight, torch.float16 --> Q8_0, shape = {14336, 4096}\n",
"INFO:hf-to-gguf:blk.14.attn_norm.weight, torch.float16 --> F32, shape = {4096}\n",
"INFO:hf-to-gguf:blk.14.ffn_norm.weight, torch.float16 --> F32, shape = {4096}\n",
"INFO:hf-to-gguf:blk.15.attn_q.weight, torch.float16 --> Q8_0, shape = {4096, 4096}\n",
"INFO:hf-to-gguf:blk.15.attn_k.weight, torch.float16 --> Q8_0, shape = {4096, 1024}\n",
"INFO:hf-to-gguf:blk.15.attn_v.weight, torch.float16 --> Q8_0, shape = {4096, 1024}\n",
"INFO:hf-to-gguf:blk.15.attn_output.weight, torch.float16 --> Q8_0, shape = {4096, 4096}\n",
"INFO:hf-to-gguf:blk.15.ffn_gate.weight, torch.float16 --> Q8_0, shape = {4096, 14336}\n",
"INFO:hf-to-gguf:blk.15.ffn_up.weight, torch.float16 --> Q8_0, shape = {4096, 14336}\n",
"INFO:hf-to-gguf:blk.15.ffn_down.weight, torch.float16 --> Q8_0, shape = {14336, 4096}\n",
"INFO:hf-to-gguf:blk.15.attn_norm.weight, torch.float16 --> F32, shape = {4096}\n",
"INFO:hf-to-gguf:blk.15.ffn_norm.weight, torch.float16 --> F32, shape = {4096}\n",
"INFO:hf-to-gguf:blk.16.attn_q.weight, torch.float16 --> Q8_0, shape = {4096, 4096}\n",
"INFO:hf-to-gguf:blk.16.attn_k.weight, torch.float16 --> Q8_0, shape = {4096, 1024}\n",
"INFO:hf-to-gguf:blk.16.attn_v.weight, torch.float16 --> Q8_0, shape = {4096, 1024}\n",
"INFO:hf-to-gguf:blk.16.attn_output.weight, torch.float16 --> Q8_0, shape = {4096, 4096}\n",
"INFO:hf-to-gguf:blk.16.ffn_gate.weight, torch.float16 --> Q8_0, shape = {4096, 14336}\n",
"INFO:hf-to-gguf:blk.16.ffn_up.weight, torch.float16 --> Q8_0, shape = {4096, 14336}\n",
"INFO:hf-to-gguf:blk.16.ffn_down.weight, torch.float16 --> Q8_0, shape = {14336, 4096}\n",
"INFO:hf-to-gguf:blk.16.attn_norm.weight, torch.float16 --> F32, shape = {4096}\n",
"INFO:hf-to-gguf:blk.16.ffn_norm.weight, torch.float16 --> F32, shape = {4096}\n",
"INFO:hf-to-gguf:blk.17.attn_q.weight, torch.float16 --> Q8_0, shape = {4096, 4096}\n",
"INFO:hf-to-gguf:blk.17.attn_k.weight, torch.float16 --> Q8_0, shape = {4096, 1024}\n",
"INFO:hf-to-gguf:blk.17.attn_v.weight, torch.float16 --> Q8_0, shape = {4096, 1024}\n",
"INFO:hf-to-gguf:blk.17.attn_output.weight, torch.float16 --> Q8_0, shape = {4096, 4096}\n",
"INFO:hf-to-gguf:blk.17.ffn_gate.weight, torch.float16 --> Q8_0, shape = {4096, 14336}\n",
"INFO:hf-to-gguf:blk.17.ffn_up.weight, torch.float16 --> Q8_0, shape = {4096, 14336}\n",
"INFO:hf-to-gguf:blk.17.ffn_down.weight, torch.float16 --> Q8_0, shape = {14336, 4096}\n",
"INFO:hf-to-gguf:blk.17.attn_norm.weight, torch.float16 --> F32, shape = {4096}\n",
"INFO:hf-to-gguf:blk.17.ffn_norm.weight, torch.float16 --> F32, shape = {4096}\n",
"INFO:hf-to-gguf:blk.18.attn_q.weight, torch.float16 --> Q8_0, shape = {4096, 4096}\n",
"INFO:hf-to-gguf:blk.18.attn_k.weight, torch.float16 --> Q8_0, shape = {4096, 1024}\n",
"INFO:hf-to-gguf:blk.18.attn_v.weight, torch.float16 --> Q8_0, shape = {4096, 1024}\n",
"INFO:hf-to-gguf:blk.18.attn_output.weight, torch.float16 --> Q8_0, shape = {4096, 4096}\n",
"INFO:hf-to-gguf:blk.18.ffn_gate.weight, torch.float16 --> Q8_0, shape = {4096, 14336}\n",
"INFO:hf-to-gguf:blk.18.ffn_up.weight, torch.float16 --> Q8_0, shape = {4096, 14336}\n",
"INFO:hf-to-gguf:blk.18.ffn_down.weight, torch.float16 --> Q8_0, shape = {14336, 4096}\n",
"INFO:hf-to-gguf:blk.18.attn_norm.weight, torch.float16 --> F32, shape = {4096}\n",
"INFO:hf-to-gguf:blk.18.ffn_norm.weight, torch.float16 --> F32, shape = {4096}\n",
"INFO:hf-to-gguf:blk.19.attn_q.weight, torch.float16 --> Q8_0, shape = {4096, 4096}\n",
"INFO:hf-to-gguf:blk.19.attn_k.weight, torch.float16 --> Q8_0, shape = {4096, 1024}\n",
"INFO:hf-to-gguf:blk.19.attn_v.weight, torch.float16 --> Q8_0, shape = {4096, 1024}\n",
"INFO:hf-to-gguf:blk.19.attn_output.weight, torch.float16 --> Q8_0, shape = {4096, 4096}\n",
"INFO:hf-to-gguf:blk.19.ffn_gate.weight, torch.float16 --> Q8_0, shape = {4096, 14336}\n",
"INFO:hf-to-gguf:blk.19.ffn_up.weight, torch.float16 --> Q8_0, shape = {4096, 14336}\n",
"INFO:hf-to-gguf:blk.19.ffn_down.weight, torch.float16 --> Q8_0, shape = {14336, 4096}\n",
"INFO:hf-to-gguf:blk.19.attn_norm.weight, torch.float16 --> F32, shape = {4096}\n",
"INFO:hf-to-gguf:blk.19.ffn_norm.weight, torch.float16 --> F32, shape = {4096}\n",
"INFO:hf-to-gguf:blk.20.attn_q.weight, torch.float16 --> Q8_0, shape = {4096, 4096}\n",
"INFO:hf-to-gguf:blk.20.attn_k.weight, torch.float16 --> Q8_0, shape = {4096, 1024}\n",
"INFO:hf-to-gguf:blk.20.attn_v.weight, torch.float16 --> Q8_0, shape = {4096, 1024}\n",
"INFO:hf-to-gguf:blk.20.attn_output.weight, torch.float16 --> Q8_0, shape = {4096, 4096}\n",
"INFO:hf-to-gguf:blk.20.ffn_gate.weight, torch.float16 --> Q8_0, shape = {4096, 14336}\n",
"INFO:hf-to-gguf:blk.20.ffn_up.weight, torch.float16 --> Q8_0, shape = {4096, 14336}\n",
"INFO:hf-to-gguf:blk.20.ffn_down.weight, torch.float16 --> Q8_0, shape = {14336, 4096}\n",
"INFO:hf-to-gguf:blk.20.attn_norm.weight, torch.float16 --> F32, shape = {4096}\n",
"INFO:hf-to-gguf:blk.20.ffn_norm.weight, torch.float16 --> F32, shape = {4096}\n",
"INFO:hf-to-gguf:blk.21.attn_q.weight, torch.float16 --> Q8_0, shape = {4096, 4096}\n",
"INFO:hf-to-gguf:blk.21.attn_k.weight, torch.float16 --> Q8_0, shape = {4096, 1024}\n",
"INFO:hf-to-gguf:blk.21.attn_v.weight, torch.float16 --> Q8_0, shape = {4096, 1024}\n",
"INFO:hf-to-gguf:blk.21.attn_output.weight, torch.float16 --> Q8_0, shape = {4096, 4096}\n",
"INFO:hf-to-gguf:blk.21.ffn_gate.weight, torch.float16 --> Q8_0, shape = {4096, 14336}\n",
"INFO:hf-to-gguf:blk.21.ffn_up.weight, torch.float16 --> Q8_0, shape = {4096, 14336}\n",
"INFO:hf-to-gguf:blk.21.ffn_down.weight, torch.float16 --> Q8_0, shape = {14336, 4096}\n",
"INFO:hf-to-gguf:blk.21.attn_norm.weight, torch.float16 --> F32, shape = {4096}\n",
"INFO:hf-to-gguf:blk.21.ffn_norm.weight, torch.float16 --> F32, shape = {4096}\n",
"INFO:hf-to-gguf:blk.22.attn_q.weight, torch.float16 --> Q8_0, shape = {4096, 4096}\n",
"INFO:hf-to-gguf:blk.22.attn_k.weight, torch.float16 --> Q8_0, shape = {4096, 1024}\n",
"INFO:hf-to-gguf:blk.22.attn_v.weight, torch.float16 --> Q8_0, shape = {4096, 1024}\n",
"INFO:hf-to-gguf:blk.22.attn_output.weight, torch.float16 --> Q8_0, shape = {4096, 4096}\n",
"INFO:hf-to-gguf:gguf: loading model part 'pytorch_model-00003-of-00003.bin'\n",
"INFO:hf-to-gguf:blk.22.ffn_gate.weight, torch.float16 --> Q8_0, shape = {4096, 14336}\n",
"INFO:hf-to-gguf:blk.22.ffn_up.weight, torch.float16 --> Q8_0, shape = {4096, 14336}\n",
"INFO:hf-to-gguf:blk.22.ffn_down.weight, torch.float16 --> Q8_0, shape = {14336, 4096}\n",
"INFO:hf-to-gguf:blk.22.attn_norm.weight, torch.float16 --> F32, shape = {4096}\n",
"INFO:hf-to-gguf:blk.22.ffn_norm.weight, torch.float16 --> F32, shape = {4096}\n",
"INFO:hf-to-gguf:blk.23.attn_q.weight, torch.float16 --> Q8_0, shape = {4096, 4096}\n",
"INFO:hf-to-gguf:blk.23.attn_k.weight, torch.float16 --> Q8_0, shape = {4096, 1024}\n",
"INFO:hf-to-gguf:blk.23.attn_v.weight, torch.float16 --> Q8_0, shape = {4096, 1024}\n",
"INFO:hf-to-gguf:blk.23.attn_output.weight, torch.float16 --> Q8_0, shape = {4096, 4096}\n",
"INFO:hf-to-gguf:blk.23.ffn_gate.weight, torch.float16 --> Q8_0, shape = {4096, 14336}\n",
"INFO:hf-to-gguf:blk.23.ffn_up.weight, torch.float16 --> Q8_0, shape = {4096, 14336}\n",
"INFO:hf-to-gguf:blk.23.ffn_down.weight, torch.float16 --> Q8_0, shape = {14336, 4096}\n",
"INFO:hf-to-gguf:blk.23.attn_norm.weight, torch.float16 --> F32, shape = {4096}\n",
"INFO:hf-to-gguf:blk.23.ffn_norm.weight, torch.float16 --> F32, shape = {4096}\n",
"INFO:hf-to-gguf:blk.24.attn_q.weight, torch.float16 --> Q8_0, shape = {4096, 4096}\n",
"INFO:hf-to-gguf:blk.24.attn_k.weight, torch.float16 --> Q8_0, shape = {4096, 1024}\n",
"INFO:hf-to-gguf:blk.24.attn_v.weight, torch.float16 --> Q8_0, shape = {4096, 1024}\n",
"INFO:hf-to-gguf:blk.24.attn_output.weight, torch.float16 --> Q8_0, shape = {4096, 4096}\n",
"INFO:hf-to-gguf:blk.24.ffn_gate.weight, torch.float16 --> Q8_0, shape = {4096, 14336}\n",
"INFO:hf-to-gguf:blk.24.ffn_up.weight, torch.float16 --> Q8_0, shape = {4096, 14336}\n",
"INFO:hf-to-gguf:blk.24.ffn_down.weight, torch.float16 --> Q8_0, shape = {14336, 4096}\n",
"INFO:hf-to-gguf:blk.24.attn_norm.weight, torch.float16 --> F32, shape = {4096}\n",
"INFO:hf-to-gguf:blk.24.ffn_norm.weight, torch.float16 --> F32, shape = {4096}\n",
"INFO:hf-to-gguf:blk.25.attn_q.weight, torch.float16 --> Q8_0, shape = {4096, 4096}\n",
"INFO:hf-to-gguf:blk.25.attn_k.weight, torch.float16 --> Q8_0, shape = {4096, 1024}\n",
"INFO:hf-to-gguf:blk.25.attn_v.weight, torch.float16 --> Q8_0, shape = {4096, 1024}\n",
"INFO:hf-to-gguf:blk.25.attn_output.weight, torch.float16 --> Q8_0, shape = {4096, 4096}\n",
"INFO:hf-to-gguf:blk.25.ffn_gate.weight, torch.float16 --> Q8_0, shape = {4096, 14336}\n",
"INFO:hf-to-gguf:blk.25.ffn_up.weight, torch.float16 --> Q8_0, shape = {4096, 14336}\n",
"INFO:hf-to-gguf:blk.25.ffn_down.weight, torch.float16 --> Q8_0, shape = {14336, 4096}\n",
"INFO:hf-to-gguf:blk.25.attn_norm.weight, torch.float16 --> F32, shape = {4096}\n",
"INFO:hf-to-gguf:blk.25.ffn_norm.weight, torch.float16 --> F32, shape = {4096}\n",
"INFO:hf-to-gguf:blk.26.attn_q.weight, torch.float16 --> Q8_0, shape = {4096, 4096}\n",
"INFO:hf-to-gguf:blk.26.attn_k.weight, torch.float16 --> Q8_0, shape = {4096, 1024}\n",
"INFO:hf-to-gguf:blk.26.attn_v.weight, torch.float16 --> Q8_0, shape = {4096, 1024}\n",
"INFO:hf-to-gguf:blk.26.attn_output.weight, torch.float16 --> Q8_0, shape = {4096, 4096}\n",
"INFO:hf-to-gguf:blk.26.ffn_gate.weight, torch.float16 --> Q8_0, shape = {4096, 14336}\n",
"INFO:hf-to-gguf:blk.26.ffn_up.weight, torch.float16 --> Q8_0, shape = {4096, 14336}\n",
"INFO:hf-to-gguf:blk.26.ffn_down.weight, torch.float16 --> Q8_0, shape = {14336, 4096}\n",
"INFO:hf-to-gguf:blk.26.attn_norm.weight, torch.float16 --> F32, shape = {4096}\n",
"INFO:hf-to-gguf:blk.26.ffn_norm.weight, torch.float16 --> F32, shape = {4096}\n",
"INFO:hf-to-gguf:blk.27.attn_q.weight, torch.float16 --> Q8_0, shape = {4096, 4096}\n",
"INFO:hf-to-gguf:blk.27.attn_k.weight, torch.float16 --> Q8_0, shape = {4096, 1024}\n",
"INFO:hf-to-gguf:blk.27.attn_v.weight, torch.float16 --> Q8_0, shape = {4096, 1024}\n",
"INFO:hf-to-gguf:blk.27.attn_output.weight, torch.float16 --> Q8_0, shape = {4096, 4096}\n",
"INFO:hf-to-gguf:blk.27.ffn_gate.weight, torch.float16 --> Q8_0, shape = {4096, 14336}\n",
"INFO:hf-to-gguf:blk.27.ffn_up.weight, torch.float16 --> Q8_0, shape = {4096, 14336}\n",
"INFO:hf-to-gguf:blk.27.ffn_down.weight, torch.float16 --> Q8_0, shape = {14336, 4096}\n",
"INFO:hf-to-gguf:blk.27.attn_norm.weight, torch.float16 --> F32, shape = {4096}\n",
"INFO:hf-to-gguf:blk.27.ffn_norm.weight, torch.float16 --> F32, shape = {4096}\n",
"INFO:hf-to-gguf:blk.28.attn_q.weight, torch.float16 --> Q8_0, shape = {4096, 4096}\n",
"INFO:hf-to-gguf:blk.28.attn_k.weight, torch.float16 --> Q8_0, shape = {4096, 1024}\n",
"INFO:hf-to-gguf:blk.28.attn_v.weight, torch.float16 --> Q8_0, shape = {4096, 1024}\n",
"INFO:hf-to-gguf:blk.28.attn_output.weight, torch.float16 --> Q8_0, shape = {4096, 4096}\n",
"INFO:hf-to-gguf:blk.28.ffn_gate.weight, torch.float16 --> Q8_0, shape = {4096, 14336}\n",
"INFO:hf-to-gguf:blk.28.ffn_up.weight, torch.float16 --> Q8_0, shape = {4096, 14336}\n",
"INFO:hf-to-gguf:blk.28.ffn_down.weight, torch.float16 --> Q8_0, shape = {14336, 4096}\n",
"INFO:hf-to-gguf:blk.28.attn_norm.weight, torch.float16 --> F32, shape = {4096}\n",
"INFO:hf-to-gguf:blk.28.ffn_norm.weight, torch.float16 --> F32, shape = {4096}\n",
"INFO:hf-to-gguf:blk.29.attn_q.weight, torch.float16 --> Q8_0, shape = {4096, 4096}\n",
"INFO:hf-to-gguf:blk.29.attn_k.weight, torch.float16 --> Q8_0, shape = {4096, 1024}\n",
"INFO:hf-to-gguf:blk.29.attn_v.weight, torch.float16 --> Q8_0, shape = {4096, 1024}\n",
"INFO:hf-to-gguf:blk.29.attn_output.weight, torch.float16 --> Q8_0, shape = {4096, 4096}\n",
"INFO:hf-to-gguf:blk.29.ffn_gate.weight, torch.float16 --> Q8_0, shape = {4096, 14336}\n",
"INFO:hf-to-gguf:blk.29.ffn_up.weight, torch.float16 --> Q8_0, shape = {4096, 14336}\n",
"INFO:hf-to-gguf:blk.29.ffn_down.weight, torch.float16 --> Q8_0, shape = {14336, 4096}\n",
"INFO:hf-to-gguf:blk.29.attn_norm.weight, torch.float16 --> F32, shape = {4096}\n",
"INFO:hf-to-gguf:blk.29.ffn_norm.weight, torch.float16 --> F32, shape = {4096}\n",
"INFO:hf-to-gguf:blk.30.attn_q.weight, torch.float16 --> Q8_0, shape = {4096, 4096}\n",
"INFO:hf-to-gguf:blk.30.attn_k.weight, torch.float16 --> Q8_0, shape = {4096, 1024}\n",
"INFO:hf-to-gguf:blk.30.attn_v.weight, torch.float16 --> Q8_0, shape = {4096, 1024}\n",
"INFO:hf-to-gguf:blk.30.attn_output.weight, torch.float16 --> Q8_0, shape = {4096, 4096}\n",
"INFO:hf-to-gguf:blk.30.ffn_gate.weight, torch.float16 --> Q8_0, shape = {4096, 14336}\n",
"INFO:hf-to-gguf:blk.30.ffn_up.weight, torch.float16 --> Q8_0, shape = {4096, 14336}\n",
"INFO:hf-to-gguf:blk.30.ffn_down.weight, torch.float16 --> Q8_0, shape = {14336, 4096}\n",
"INFO:hf-to-gguf:blk.30.attn_norm.weight, torch.float16 --> F32, shape = {4096}\n",
"INFO:hf-to-gguf:blk.30.ffn_norm.weight, torch.float16 --> F32, shape = {4096}\n",
"INFO:hf-to-gguf:blk.31.attn_q.weight, torch.float16 --> Q8_0, shape = {4096, 4096}\n",
"INFO:hf-to-gguf:blk.31.attn_k.weight, torch.float16 --> Q8_0, shape = {4096, 1024}\n",
"INFO:hf-to-gguf:blk.31.attn_v.weight, torch.float16 --> Q8_0, shape = {4096, 1024}\n",
"INFO:hf-to-gguf:blk.31.attn_output.weight, torch.float16 --> Q8_0, shape = {4096, 4096}\n",
"INFO:hf-to-gguf:blk.31.ffn_gate.weight, torch.float16 --> Q8_0, shape = {4096, 14336}\n",
"INFO:hf-to-gguf:blk.31.ffn_up.weight, torch.float16 --> Q8_0, shape = {4096, 14336}\n",
"INFO:hf-to-gguf:blk.31.ffn_down.weight, torch.float16 --> Q8_0, shape = {14336, 4096}\n",
"INFO:hf-to-gguf:blk.31.attn_norm.weight, torch.float16 --> F32, shape = {4096}\n",
"INFO:hf-to-gguf:blk.31.ffn_norm.weight, torch.float16 --> F32, shape = {4096}\n",
"INFO:hf-to-gguf:output_norm.weight, torch.float16 --> F32, shape = {4096}\n",
"INFO:hf-to-gguf:output.weight, torch.float16 --> Q8_0, shape = {4096, 32768}\n",
"INFO:hf-to-gguf:Set meta model\n",
"INFO:hf-to-gguf:Set model parameters\n",
"INFO:hf-to-gguf:gguf: context length = 32768\n",
"INFO:hf-to-gguf:gguf: embedding length = 4096\n",
"INFO:hf-to-gguf:gguf: feed forward length = 14336\n",
"INFO:hf-to-gguf:gguf: head count = 32\n",
"INFO:hf-to-gguf:gguf: key-value head count = 8\n",
"INFO:hf-to-gguf:gguf: rope theta = 1000000.0\n",
"INFO:hf-to-gguf:gguf: rms norm epsilon = 1e-05\n",
"INFO:hf-to-gguf:gguf: file type = 7\n",
"INFO:hf-to-gguf:Set model tokenizer\n",
"INFO:gguf.vocab:Setting special token type bos to 1\n",
"INFO:gguf.vocab:Setting special token type eos to 2\n",
"INFO:gguf.vocab:Setting special token type unk to 0\n",
"INFO:gguf.vocab:Setting special token type pad to 770\n",
"INFO:gguf.vocab:Setting add_bos_token to True\n",
"INFO:gguf.vocab:Setting add_eos_token to False\n",
"INFO:hf-to-gguf:Set model quantization version\n",
"INFO:gguf.gguf_writer:Writing the following files:\n",
"INFO:gguf.gguf_writer:/content/model/unsloth.Q8_0.gguf: n_tensors = 291, total_size = 7.7G\n",
"Writing: 100%|██████████| 7.70G/7.70G [03:48<00:00, 33.6Mbyte/s]\n",
"INFO:hf-to-gguf:Model successfully exported to /content/model/unsloth.Q8_0.gguf\n",
"Unsloth: Conversion completed! Output location: /content/model/unsloth.Q8_0.gguf\n",
"Unsloth: Merging 4bit and LoRA weights to 16bit...\n",
"Unsloth: Will use up to 5.9 out of 12.67 RAM for saving.\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"100%|██████████| 32/32 [02:44<00:00, 5.13s/it]\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Unsloth: Saving tokenizer... Done.\n",
"Unsloth: Saving model... This might take 5 minutes for Llama-7b...\n",
"Unsloth: Saving vaugheu/MistralBangla3v7b/pytorch_model-00001-of-00003.bin...\n",
"Unsloth: Saving vaugheu/MistralBangla3v7b/pytorch_model-00002-of-00003.bin...\n",
"Unsloth: Saving vaugheu/MistralBangla3v7b/pytorch_model-00003-of-00003.bin...\n",
"Done.\n",
"==((====))== Unsloth: Conversion from QLoRA to GGUF information\n",
" \\\\ /| [0] Installing llama.cpp will take 3 minutes.\n",
"O^O/ \\_/ \\ [1] Converting HF to GGUF 16bits will take 3 minutes.\n",
"\\ / [2] Converting GGUF 16bits to ['q8_0'] will take 10 minutes each.\n",
" \"-____-\" In total, you will have to wait at least 16 minutes.\n",
"\n",
"Unsloth: [0] Installing llama.cpp. This will take 3 minutes...\n",
"Unsloth: [1] Converting model at vaugheu/MistralBangla3v7b into q8_0 GGUF format.\n",
"The output location will be /content/vaugheu/MistralBangla3v7b/unsloth.Q8_0.gguf\n",
"This will take 3 minutes...\n",
"INFO:hf-to-gguf:Loading model: MistralBangla3v7b\n",
"INFO:gguf.gguf_writer:gguf: This GGUF file is for Little Endian only\n",
"INFO:hf-to-gguf:Exporting model...\n",
"INFO:hf-to-gguf:gguf: loading model weight map from 'pytorch_model.bin.index.json'\n",
"INFO:hf-to-gguf:gguf: loading model part 'pytorch_model-00001-of-00003.bin'\n",
"INFO:hf-to-gguf:token_embd.weight, torch.float16 --> Q8_0, shape = {4096, 32768}\n",
"INFO:hf-to-gguf:blk.0.attn_q.weight, torch.float16 --> Q8_0, shape = {4096, 4096}\n",
"INFO:hf-to-gguf:blk.0.attn_k.weight, torch.float16 --> Q8_0, shape = {4096, 1024}\n",
"INFO:hf-to-gguf:blk.0.attn_v.weight, torch.float16 --> Q8_0, shape = {4096, 1024}\n",
"INFO:hf-to-gguf:blk.0.attn_output.weight, torch.float16 --> Q8_0, shape = {4096, 4096}\n",
"INFO:hf-to-gguf:blk.0.ffn_gate.weight, torch.float16 --> Q8_0, shape = {4096, 14336}\n",
"INFO:hf-to-gguf:blk.0.ffn_up.weight, torch.float16 --> Q8_0, shape = {4096, 14336}\n",
"INFO:hf-to-gguf:blk.0.ffn_down.weight, torch.float16 --> Q8_0, shape = {14336, 4096}\n",
"INFO:hf-to-gguf:blk.0.attn_norm.weight, torch.float16 --> F32, shape = {4096}\n",
"INFO:hf-to-gguf:blk.0.ffn_norm.weight, torch.float16 --> F32, shape = {4096}\n",
"INFO:hf-to-gguf:blk.1.attn_q.weight, torch.float16 --> Q8_0, shape = {4096, 4096}\n",
"INFO:hf-to-gguf:blk.1.attn_k.weight, torch.float16 --> Q8_0, shape = {4096, 1024}\n",
"INFO:hf-to-gguf:blk.1.attn_v.weight, torch.float16 --> Q8_0, shape = {4096, 1024}\n",
"INFO:hf-to-gguf:blk.1.attn_output.weight, torch.float16 --> Q8_0, shape = {4096, 4096}\n",
"INFO:hf-to-gguf:blk.1.ffn_gate.weight, torch.float16 --> Q8_0, shape = {4096, 14336}\n",
"INFO:hf-to-gguf:blk.1.ffn_up.weight, torch.float16 --> Q8_0, shape = {4096, 14336}\n",
"INFO:hf-to-gguf:blk.1.ffn_down.weight, torch.float16 --> Q8_0, shape = {14336, 4096}\n",
"INFO:hf-to-gguf:blk.1.attn_norm.weight, torch.float16 --> F32, shape = {4096}\n",
"INFO:hf-to-gguf:blk.1.ffn_norm.weight, torch.float16 --> F32, shape = {4096}\n",
"INFO:hf-to-gguf:blk.2.attn_q.weight, torch.float16 --> Q8_0, shape = {4096, 4096}\n",
"INFO:hf-to-gguf:blk.2.attn_k.weight, torch.float16 --> Q8_0, shape = {4096, 1024}\n",
"INFO:hf-to-gguf:blk.2.attn_v.weight, torch.float16 --> Q8_0, shape = {4096, 1024}\n",
"INFO:hf-to-gguf:blk.2.attn_output.weight, torch.float16 --> Q8_0, shape = {4096, 4096}\n",
"INFO:hf-to-gguf:blk.2.ffn_gate.weight, torch.float16 --> Q8_0, shape = {4096, 14336}\n",
"INFO:hf-to-gguf:blk.2.ffn_up.weight, torch.float16 --> Q8_0, shape = {4096, 14336}\n",
"INFO:hf-to-gguf:blk.2.ffn_down.weight, torch.float16 --> Q8_0, shape = {14336, 4096}\n",
"INFO:hf-to-gguf:blk.2.attn_norm.weight, torch.float16 --> F32, shape = {4096}\n",
"INFO:hf-to-gguf:blk.2.ffn_norm.weight, torch.float16 --> F32, shape = {4096}\n",
"INFO:hf-to-gguf:blk.3.attn_q.weight, torch.float16 --> Q8_0, shape = {4096, 4096}\n",
"INFO:hf-to-gguf:blk.3.attn_k.weight, torch.float16 --> Q8_0, shape = {4096, 1024}\n",
"INFO:hf-to-gguf:blk.3.attn_v.weight, torch.float16 --> Q8_0, shape = {4096, 1024}\n",
"INFO:hf-to-gguf:blk.3.attn_output.weight, torch.float16 --> Q8_0, shape = {4096, 4096}\n",
"INFO:hf-to-gguf:blk.3.ffn_gate.weight, torch.float16 --> Q8_0, shape = {4096, 14336}\n",
"INFO:hf-to-gguf:blk.3.ffn_up.weight, torch.float16 --> Q8_0, shape = {4096, 14336}\n",
"INFO:hf-to-gguf:blk.3.ffn_down.weight, torch.float16 --> Q8_0, shape = {14336, 4096}\n",
"INFO:hf-to-gguf:blk.3.attn_norm.weight, torch.float16 --> F32, shape = {4096}\n",
"INFO:hf-to-gguf:blk.3.ffn_norm.weight, torch.float16 --> F32, shape = {4096}\n",
"INFO:hf-to-gguf:blk.4.attn_q.weight, torch.float16 --> Q8_0, shape = {4096, 4096}\n",
"INFO:hf-to-gguf:blk.4.attn_k.weight, torch.float16 --> Q8_0, shape = {4096, 1024}\n",
"INFO:hf-to-gguf:blk.4.attn_v.weight, torch.float16 --> Q8_0, shape = {4096, 1024}\n",
"INFO:hf-to-gguf:blk.4.attn_output.weight, torch.float16 --> Q8_0, shape = {4096, 4096}\n",
"INFO:hf-to-gguf:blk.4.ffn_gate.weight, torch.float16 --> Q8_0, shape = {4096, 14336}\n",
"INFO:hf-to-gguf:blk.4.ffn_up.weight, torch.float16 --> Q8_0, shape = {4096, 14336}\n",
"INFO:hf-to-gguf:blk.4.ffn_down.weight, torch.float16 --> Q8_0, shape = {14336, 4096}\n",
"INFO:hf-to-gguf:blk.4.attn_norm.weight, torch.float16 --> F32, shape = {4096}\n",
"INFO:hf-to-gguf:blk.4.ffn_norm.weight, torch.float16 --> F32, shape = {4096}\n",
"INFO:hf-to-gguf:blk.5.attn_q.weight, torch.float16 --> Q8_0, shape = {4096, 4096}\n",
"INFO:hf-to-gguf:blk.5.attn_k.weight, torch.float16 --> Q8_0, shape = {4096, 1024}\n",
"INFO:hf-to-gguf:blk.5.attn_v.weight, torch.float16 --> Q8_0, shape = {4096, 1024}\n",
"INFO:hf-to-gguf:blk.5.attn_output.weight, torch.float16 --> Q8_0, shape = {4096, 4096}\n",
"INFO:hf-to-gguf:blk.5.ffn_gate.weight, torch.float16 --> Q8_0, shape = {4096, 14336}\n",
"INFO:hf-to-gguf:blk.5.ffn_up.weight, torch.float16 --> Q8_0, shape = {4096, 14336}\n",
"INFO:hf-to-gguf:blk.5.ffn_down.weight, torch.float16 --> Q8_0, shape = {14336, 4096}\n",
"INFO:hf-to-gguf:blk.5.attn_norm.weight, torch.float16 --> F32, shape = {4096}\n",
"INFO:hf-to-gguf:blk.5.ffn_norm.weight, torch.float16 --> F32, shape = {4096}\n",
"INFO:hf-to-gguf:blk.6.attn_q.weight, torch.float16 --> Q8_0, shape = {4096, 4096}\n",
"INFO:hf-to-gguf:blk.6.attn_k.weight, torch.float16 --> Q8_0, shape = {4096, 1024}\n",
"INFO:hf-to-gguf:blk.6.attn_v.weight, torch.float16 --> Q8_0, shape = {4096, 1024}\n",
"INFO:hf-to-gguf:blk.6.attn_output.weight, torch.float16 --> Q8_0, shape = {4096, 4096}\n",
"INFO:hf-to-gguf:blk.6.ffn_gate.weight, torch.float16 --> Q8_0, shape = {4096, 14336}\n",
"INFO:hf-to-gguf:blk.6.ffn_up.weight, torch.float16 --> Q8_0, shape = {4096, 14336}\n",
"INFO:hf-to-gguf:blk.6.ffn_down.weight, torch.float16 --> Q8_0, shape = {14336, 4096}\n",
"INFO:hf-to-gguf:blk.6.attn_norm.weight, torch.float16 --> F32, shape = {4096}\n",
"INFO:hf-to-gguf:blk.6.ffn_norm.weight, torch.float16 --> F32, shape = {4096}\n",
"INFO:hf-to-gguf:blk.7.attn_q.weight, torch.float16 --> Q8_0, shape = {4096, 4096}\n",
"INFO:hf-to-gguf:blk.7.attn_k.weight, torch.float16 --> Q8_0, shape = {4096, 1024}\n",
"INFO:hf-to-gguf:blk.7.attn_v.weight, torch.float16 --> Q8_0, shape = {4096, 1024}\n",
"INFO:hf-to-gguf:blk.7.attn_output.weight, torch.float16 --> Q8_0, shape = {4096, 4096}\n",
"INFO:hf-to-gguf:blk.7.ffn_gate.weight, torch.float16 --> Q8_0, shape = {4096, 14336}\n",
"INFO:hf-to-gguf:blk.7.ffn_up.weight, torch.float16 --> Q8_0, shape = {4096, 14336}\n",
"INFO:hf-to-gguf:blk.7.ffn_down.weight, torch.float16 --> Q8_0, shape = {14336, 4096}\n",
"INFO:hf-to-gguf:blk.7.attn_norm.weight, torch.float16 --> F32, shape = {4096}\n",
"INFO:hf-to-gguf:blk.7.ffn_norm.weight, torch.float16 --> F32, shape = {4096}\n",
"INFO:hf-to-gguf:blk.8.attn_q.weight, torch.float16 --> Q8_0, shape = {4096, 4096}\n",
"INFO:hf-to-gguf:blk.8.attn_k.weight, torch.float16 --> Q8_0, shape = {4096, 1024}\n",
"INFO:hf-to-gguf:blk.8.attn_v.weight, torch.float16 --> Q8_0, shape = {4096, 1024}\n",
"INFO:hf-to-gguf:blk.8.attn_output.weight, torch.float16 --> Q8_0, shape = {4096, 4096}\n",
"INFO:hf-to-gguf:blk.8.ffn_gate.weight, torch.float16 --> Q8_0, shape = {4096, 14336}\n",
"INFO:hf-to-gguf:blk.8.ffn_up.weight, torch.float16 --> Q8_0, shape = {4096, 14336}\n",
"INFO:hf-to-gguf:blk.8.ffn_down.weight, torch.float16 --> Q8_0, shape = {14336, 4096}\n",
"INFO:hf-to-gguf:blk.8.attn_norm.weight, torch.float16 --> F32, shape = {4096}\n",
"INFO:hf-to-gguf:blk.8.ffn_norm.weight, torch.float16 --> F32, shape = {4096}\n",
"INFO:hf-to-gguf:blk.9.attn_q.weight, torch.float16 --> Q8_0, shape = {4096, 4096}\n",
"INFO:hf-to-gguf:blk.9.attn_k.weight, torch.float16 --> Q8_0, shape = {4096, 1024}\n",
"INFO:hf-to-gguf:blk.9.attn_v.weight, torch.float16 --> Q8_0, shape = {4096, 1024}\n",
"INFO:hf-to-gguf:blk.9.attn_output.weight, torch.float16 --> Q8_0, shape = {4096, 4096}\n",
"INFO:hf-to-gguf:blk.9.ffn_gate.weight, torch.float16 --> Q8_0, shape = {4096, 14336}\n",
"INFO:hf-to-gguf:blk.9.ffn_up.weight, torch.float16 --> Q8_0, shape = {4096, 14336}\n",
"INFO:hf-to-gguf:blk.9.ffn_down.weight, torch.float16 --> Q8_0, shape = {14336, 4096}\n",
"INFO:hf-to-gguf:blk.9.attn_norm.weight, torch.float16 --> F32, shape = {4096}\n",
"INFO:hf-to-gguf:blk.9.ffn_norm.weight, torch.float16 --> F32, shape = {4096}\n",
"INFO:hf-to-gguf:blk.10.attn_q.weight, torch.float16 --> Q8_0, shape = {4096, 4096}\n",
"INFO:hf-to-gguf:blk.10.attn_k.weight, torch.float16 --> Q8_0, shape = {4096, 1024}\n",
"INFO:hf-to-gguf:blk.10.attn_v.weight, torch.float16 --> Q8_0, shape = {4096, 1024}\n",
"INFO:hf-to-gguf:blk.10.attn_output.weight, torch.float16 --> Q8_0, shape = {4096, 4096}\n",
"INFO:hf-to-gguf:blk.10.ffn_gate.weight, torch.float16 --> Q8_0, shape = {4096, 14336}\n",
"INFO:hf-to-gguf:blk.10.ffn_up.weight, torch.float16 --> Q8_0, shape = {4096, 14336}\n",
"INFO:hf-to-gguf:gguf: loading model part 'pytorch_model-00002-of-00003.bin'\n",
"INFO:hf-to-gguf:blk.10.ffn_down.weight, torch.float16 --> Q8_0, shape = {14336, 4096}\n",
"INFO:hf-to-gguf:blk.10.attn_norm.weight, torch.float16 --> F32, shape = {4096}\n",
"INFO:hf-to-gguf:blk.10.ffn_norm.weight, torch.float16 --> F32, shape = {4096}\n",
"INFO:hf-to-gguf:blk.11.attn_q.weight, torch.float16 --> Q8_0, shape = {4096, 4096}\n",
"INFO:hf-to-gguf:blk.11.attn_k.weight, torch.float16 --> Q8_0, shape = {4096, 1024}\n",
"INFO:hf-to-gguf:blk.11.attn_v.weight, torch.float16 --> Q8_0, shape = {4096, 1024}\n",
"INFO:hf-to-gguf:blk.11.attn_output.weight, torch.float16 --> Q8_0, shape = {4096, 4096}\n",
"INFO:hf-to-gguf:blk.11.ffn_gate.weight, torch.float16 --> Q8_0, shape = {4096, 14336}\n",
"INFO:hf-to-gguf:blk.11.ffn_up.weight, torch.float16 --> Q8_0, shape = {4096, 14336}\n",
"INFO:hf-to-gguf:blk.11.ffn_down.weight, torch.float16 --> Q8_0, shape = {14336, 4096}\n",
"INFO:hf-to-gguf:blk.11.attn_norm.weight, torch.float16 --> F32, shape = {4096}\n",
"INFO:hf-to-gguf:blk.11.ffn_norm.weight, torch.float16 --> F32, shape = {4096}\n",
"INFO:hf-to-gguf:blk.12.attn_q.weight, torch.float16 --> Q8_0, shape = {4096, 4096}\n",
"INFO:hf-to-gguf:blk.12.attn_k.weight, torch.float16 --> Q8_0, shape = {4096, 1024}\n",
"INFO:hf-to-gguf:blk.12.attn_v.weight, torch.float16 --> Q8_0, shape = {4096, 1024}\n",
"INFO:hf-to-gguf:blk.12.attn_output.weight, torch.float16 --> Q8_0, shape = {4096, 4096}\n",
"INFO:hf-to-gguf:blk.12.ffn_gate.weight, torch.float16 --> Q8_0, shape = {4096, 14336}\n",
"INFO:hf-to-gguf:blk.12.ffn_up.weight, torch.float16 --> Q8_0, shape = {4096, 14336}\n",
"INFO:hf-to-gguf:blk.12.ffn_down.weight, torch.float16 --> Q8_0, shape = {14336, 4096}\n",
"INFO:hf-to-gguf:blk.12.attn_norm.weight, torch.float16 --> F32, shape = {4096}\n",
"INFO:hf-to-gguf:blk.12.ffn_norm.weight, torch.float16 --> F32, shape = {4096}\n",
"INFO:hf-to-gguf:blk.13.attn_q.weight, torch.float16 --> Q8_0, shape = {4096, 4096}\n",
"INFO:hf-to-gguf:blk.13.attn_k.weight, torch.float16 --> Q8_0, shape = {4096, 1024}\n",
"INFO:hf-to-gguf:blk.13.attn_v.weight, torch.float16 --> Q8_0, shape = {4096, 1024}\n",
"INFO:hf-to-gguf:blk.13.attn_output.weight, torch.float16 --> Q8_0, shape = {4096, 4096}\n",
"INFO:hf-to-gguf:blk.13.ffn_gate.weight, torch.float16 --> Q8_0, shape = {4096, 14336}\n",
"INFO:hf-to-gguf:blk.13.ffn_up.weight, torch.float16 --> Q8_0, shape = {4096, 14336}\n",
"INFO:hf-to-gguf:blk.13.ffn_down.weight, torch.float16 --> Q8_0, shape = {14336, 4096}\n",
"INFO:hf-to-gguf:blk.13.attn_norm.weight, torch.float16 --> F32, shape = {4096}\n",
"INFO:hf-to-gguf:blk.13.ffn_norm.weight, torch.float16 --> F32, shape = {4096}\n",
"INFO:hf-to-gguf:blk.14.attn_q.weight, torch.float16 --> Q8_0, shape = {4096, 4096}\n",
"INFO:hf-to-gguf:blk.14.attn_k.weight, torch.float16 --> Q8_0, shape = {4096, 1024}\n",
"INFO:hf-to-gguf:blk.14.attn_v.weight, torch.float16 --> Q8_0, shape = {4096, 1024}\n",
"INFO:hf-to-gguf:blk.14.attn_output.weight, torch.float16 --> Q8_0, shape = {4096, 4096}\n",
"INFO:hf-to-gguf:blk.14.ffn_gate.weight, torch.float16 --> Q8_0, shape = {4096, 14336}\n",
"INFO:hf-to-gguf:blk.14.ffn_up.weight, torch.float16 --> Q8_0, shape = {4096, 14336}\n",
"INFO:hf-to-gguf:blk.14.ffn_down.weight, torch.float16 --> Q8_0, shape = {14336, 4096}\n",
"INFO:hf-to-gguf:blk.14.attn_norm.weight, torch.float16 --> F32, shape = {4096}\n",
"INFO:hf-to-gguf:blk.14.ffn_norm.weight, torch.float16 --> F32, shape = {4096}\n",
"INFO:hf-to-gguf:blk.15.attn_q.weight, torch.float16 --> Q8_0, shape = {4096, 4096}\n",
"INFO:hf-to-gguf:blk.15.attn_k.weight, torch.float16 --> Q8_0, shape = {4096, 1024}\n",
"INFO:hf-to-gguf:blk.15.attn_v.weight, torch.float16 --> Q8_0, shape = {4096, 1024}\n",
"INFO:hf-to-gguf:blk.15.attn_output.weight, torch.float16 --> Q8_0, shape = {4096, 4096}\n",
"INFO:hf-to-gguf:blk.15.ffn_gate.weight, torch.float16 --> Q8_0, shape = {4096, 14336}\n",
"INFO:hf-to-gguf:blk.15.ffn_up.weight, torch.float16 --> Q8_0, shape = {4096, 14336}\n",
"INFO:hf-to-gguf:blk.15.ffn_down.weight, torch.float16 --> Q8_0, shape = {14336, 4096}\n",
"INFO:hf-to-gguf:blk.15.attn_norm.weight, torch.float16 --> F32, shape = {4096}\n",
"INFO:hf-to-gguf:blk.15.ffn_norm.weight, torch.float16 --> F32, shape = {4096}\n",
"INFO:hf-to-gguf:blk.16.attn_q.weight, torch.float16 --> Q8_0, shape = {4096, 4096}\n",
"INFO:hf-to-gguf:blk.16.attn_k.weight, torch.float16 --> Q8_0, shape = {4096, 1024}\n",
"INFO:hf-to-gguf:blk.16.attn_v.weight, torch.float16 --> Q8_0, shape = {4096, 1024}\n",
"INFO:hf-to-gguf:blk.16.attn_output.weight, torch.float16 --> Q8_0, shape = {4096, 4096}\n",
"INFO:hf-to-gguf:blk.16.ffn_gate.weight, torch.float16 --> Q8_0, shape = {4096, 14336}\n",
"INFO:hf-to-gguf:blk.16.ffn_up.weight, torch.float16 --> Q8_0, shape = {4096, 14336}\n",
"INFO:hf-to-gguf:blk.16.ffn_down.weight, torch.float16 --> Q8_0, shape = {14336, 4096}\n",
"INFO:hf-to-gguf:blk.16.attn_norm.weight, torch.float16 --> F32, shape = {4096}\n",
"INFO:hf-to-gguf:blk.16.ffn_norm.weight, torch.float16 --> F32, shape = {4096}\n",
"INFO:hf-to-gguf:blk.17.attn_q.weight, torch.float16 --> Q8_0, shape = {4096, 4096}\n",
"INFO:hf-to-gguf:blk.17.attn_k.weight, torch.float16 --> Q8_0, shape = {4096, 1024}\n",
"INFO:hf-to-gguf:blk.17.attn_v.weight, torch.float16 --> Q8_0, shape = {4096, 1024}\n",
"INFO:hf-to-gguf:blk.17.attn_output.weight, torch.float16 --> Q8_0, shape = {4096, 4096}\n",
"INFO:hf-to-gguf:blk.17.ffn_gate.weight, torch.float16 --> Q8_0, shape = {4096, 14336}\n",
"INFO:hf-to-gguf:blk.17.ffn_up.weight, torch.float16 --> Q8_0, shape = {4096, 14336}\n",
"INFO:hf-to-gguf:blk.17.ffn_down.weight, torch.float16 --> Q8_0, shape = {14336, 4096}\n",
"INFO:hf-to-gguf:blk.17.attn_norm.weight, torch.float16 --> F32, shape = {4096}\n",
"INFO:hf-to-gguf:blk.17.ffn_norm.weight, torch.float16 --> F32, shape = {4096}\n",
"INFO:hf-to-gguf:blk.18.attn_q.weight, torch.float16 --> Q8_0, shape = {4096, 4096}\n",
"INFO:hf-to-gguf:blk.18.attn_k.weight, torch.float16 --> Q8_0, shape = {4096, 1024}\n",
"INFO:hf-to-gguf:blk.18.attn_v.weight, torch.float16 --> Q8_0, shape = {4096, 1024}\n",
"INFO:hf-to-gguf:blk.18.attn_output.weight, torch.float16 --> Q8_0, shape = {4096, 4096}\n",
"INFO:hf-to-gguf:blk.18.ffn_gate.weight, torch.float16 --> Q8_0, shape = {4096, 14336}\n",
"INFO:hf-to-gguf:blk.18.ffn_up.weight, torch.float16 --> Q8_0, shape = {4096, 14336}\n",
"INFO:hf-to-gguf:blk.18.ffn_down.weight, torch.float16 --> Q8_0, shape = {14336, 4096}\n",
"INFO:hf-to-gguf:blk.18.attn_norm.weight, torch.float16 --> F32, shape = {4096}\n",
"INFO:hf-to-gguf:blk.18.ffn_norm.weight, torch.float16 --> F32, shape = {4096}\n",
"INFO:hf-to-gguf:blk.19.attn_q.weight, torch.float16 --> Q8_0, shape = {4096, 4096}\n",
"INFO:hf-to-gguf:blk.19.attn_k.weight, torch.float16 --> Q8_0, shape = {4096, 1024}\n",
"INFO:hf-to-gguf:blk.19.attn_v.weight, torch.float16 --> Q8_0, shape = {4096, 1024}\n",
"INFO:hf-to-gguf:blk.19.attn_output.weight, torch.float16 --> Q8_0, shape = {4096, 4096}\n",
"INFO:hf-to-gguf:blk.19.ffn_gate.weight, torch.float16 --> Q8_0, shape = {4096, 14336}\n",
"INFO:hf-to-gguf:blk.19.ffn_up.weight, torch.float16 --> Q8_0, shape = {4096, 14336}\n",
"INFO:hf-to-gguf:blk.19.ffn_down.weight, torch.float16 --> Q8_0, shape = {14336, 4096}\n",
"INFO:hf-to-gguf:blk.19.attn_norm.weight, torch.float16 --> F32, shape = {4096}\n",
"INFO:hf-to-gguf:blk.19.ffn_norm.weight, torch.float16 --> F32, shape = {4096}\n",
"INFO:hf-to-gguf:blk.20.attn_q.weight, torch.float16 --> Q8_0, shape = {4096, 4096}\n",
"INFO:hf-to-gguf:blk.20.attn_k.weight, torch.float16 --> Q8_0, shape = {4096, 1024}\n",
"INFO:hf-to-gguf:blk.20.attn_v.weight, torch.float16 --> Q8_0, shape = {4096, 1024}\n",
"INFO:hf-to-gguf:blk.20.attn_output.weight, torch.float16 --> Q8_0, shape = {4096, 4096}\n",
"INFO:hf-to-gguf:blk.20.ffn_gate.weight, torch.float16 --> Q8_0, shape = {4096, 14336}\n",
"INFO:hf-to-gguf:blk.20.ffn_up.weight, torch.float16 --> Q8_0, shape = {4096, 14336}\n",
"INFO:hf-to-gguf:blk.20.ffn_down.weight, torch.float16 --> Q8_0, shape = {14336, 4096}\n",
"INFO:hf-to-gguf:blk.20.attn_norm.weight, torch.float16 --> F32, shape = {4096}\n",
"INFO:hf-to-gguf:blk.20.ffn_norm.weight, torch.float16 --> F32, shape = {4096}\n",
"INFO:hf-to-gguf:blk.21.attn_q.weight, torch.float16 --> Q8_0, shape = {4096, 4096}\n",
"INFO:hf-to-gguf:blk.21.attn_k.weight, torch.float16 --> Q8_0, shape = {4096, 1024}\n",
"INFO:hf-to-gguf:blk.21.attn_v.weight, torch.float16 --> Q8_0, shape = {4096, 1024}\n",
"INFO:hf-to-gguf:blk.21.attn_output.weight, torch.float16 --> Q8_0, shape = {4096, 4096}\n",
"INFO:hf-to-gguf:blk.21.ffn_gate.weight, torch.float16 --> Q8_0, shape = {4096, 14336}\n",
"INFO:hf-to-gguf:blk.21.ffn_up.weight, torch.float16 --> Q8_0, shape = {4096, 14336}\n",
"INFO:hf-to-gguf:blk.21.ffn_down.weight, torch.float16 --> Q8_0, shape = {14336, 4096}\n",
"INFO:hf-to-gguf:blk.21.attn_norm.weight, torch.float16 --> F32, shape = {4096}\n",
"INFO:hf-to-gguf:blk.21.ffn_norm.weight, torch.float16 --> F32, shape = {4096}\n",
"INFO:hf-to-gguf:blk.22.attn_q.weight, torch.float16 --> Q8_0, shape = {4096, 4096}\n",
"INFO:hf-to-gguf:blk.22.attn_k.weight, torch.float16 --> Q8_0, shape = {4096, 1024}\n",
"INFO:hf-to-gguf:blk.22.attn_v.weight, torch.float16 --> Q8_0, shape = {4096, 1024}\n",
"INFO:hf-to-gguf:blk.22.attn_output.weight, torch.float16 --> Q8_0, shape = {4096, 4096}\n",
"INFO:hf-to-gguf:gguf: loading model part 'pytorch_model-00003-of-00003.bin'\n",
"INFO:hf-to-gguf:blk.22.ffn_gate.weight, torch.float16 --> Q8_0, shape = {4096, 14336}\n",
"INFO:hf-to-gguf:blk.22.ffn_up.weight, torch.float16 --> Q8_0, shape = {4096, 14336}\n",
"INFO:hf-to-gguf:blk.22.ffn_down.weight, torch.float16 --> Q8_0, shape = {14336, 4096}\n",
"INFO:hf-to-gguf:blk.22.attn_norm.weight, torch.float16 --> F32, shape = {4096}\n",
"INFO:hf-to-gguf:blk.22.ffn_norm.weight, torch.float16 --> F32, shape = {4096}\n",
"INFO:hf-to-gguf:blk.23.attn_q.weight, torch.float16 --> Q8_0, shape = {4096, 4096}\n",
"INFO:hf-to-gguf:blk.23.attn_k.weight, torch.float16 --> Q8_0, shape = {4096, 1024}\n",
"INFO:hf-to-gguf:blk.23.attn_v.weight, torch.float16 --> Q8_0, shape = {4096, 1024}\n",
"INFO:hf-to-gguf:blk.23.attn_output.weight, torch.float16 --> Q8_0, shape = {4096, 4096}\n",
"INFO:hf-to-gguf:blk.23.ffn_gate.weight, torch.float16 --> Q8_0, shape = {4096, 14336}\n",
"INFO:hf-to-gguf:blk.23.ffn_up.weight, torch.float16 --> Q8_0, shape = {4096, 14336}\n",
"INFO:hf-to-gguf:blk.23.ffn_down.weight, torch.float16 --> Q8_0, shape = {14336, 4096}\n",
"INFO:hf-to-gguf:blk.23.attn_norm.weight, torch.float16 --> F32, shape = {4096}\n",
"INFO:hf-to-gguf:blk.23.ffn_norm.weight, torch.float16 --> F32, shape = {4096}\n",
"INFO:hf-to-gguf:blk.24.attn_q.weight, torch.float16 --> Q8_0, shape = {4096, 4096}\n",
"INFO:hf-to-gguf:blk.24.attn_k.weight, torch.float16 --> Q8_0, shape = {4096, 1024}\n",
"INFO:hf-to-gguf:blk.24.attn_v.weight, torch.float16 --> Q8_0, shape = {4096, 1024}\n",
"INFO:hf-to-gguf:blk.24.attn_output.weight, torch.float16 --> Q8_0, shape = {4096, 4096}\n",
"INFO:hf-to-gguf:blk.24.ffn_gate.weight, torch.float16 --> Q8_0, shape = {4096, 14336}\n",
"INFO:hf-to-gguf:blk.24.ffn_up.weight, torch.float16 --> Q8_0, shape = {4096, 14336}\n",
"INFO:hf-to-gguf:blk.24.ffn_down.weight, torch.float16 --> Q8_0, shape = {14336, 4096}\n",
"INFO:hf-to-gguf:blk.24.attn_norm.weight, torch.float16 --> F32, shape = {4096}\n",
"INFO:hf-to-gguf:blk.24.ffn_norm.weight, torch.float16 --> F32, shape = {4096}\n",
"INFO:hf-to-gguf:blk.25.attn_q.weight, torch.float16 --> Q8_0, shape = {4096, 4096}\n",
"INFO:hf-to-gguf:blk.25.attn_k.weight, torch.float16 --> Q8_0, shape = {4096, 1024}\n",
"INFO:hf-to-gguf:blk.25.attn_v.weight, torch.float16 --> Q8_0, shape = {4096, 1024}\n",
"INFO:hf-to-gguf:blk.25.attn_output.weight, torch.float16 --> Q8_0, shape = {4096, 4096}\n",
"INFO:hf-to-gguf:blk.25.ffn_gate.weight, torch.float16 --> Q8_0, shape = {4096, 14336}\n",
"INFO:hf-to-gguf:blk.25.ffn_up.weight, torch.float16 --> Q8_0, shape = {4096, 14336}\n",
"INFO:hf-to-gguf:blk.25.ffn_down.weight, torch.float16 --> Q8_0, shape = {14336, 4096}\n",
"INFO:hf-to-gguf:blk.25.attn_norm.weight, torch.float16 --> F32, shape = {4096}\n",
"INFO:hf-to-gguf:blk.25.ffn_norm.weight, torch.float16 --> F32, shape = {4096}\n",
"INFO:hf-to-gguf:blk.26.attn_q.weight, torch.float16 --> Q8_0, shape = {4096, 4096}\n",
"INFO:hf-to-gguf:blk.26.attn_k.weight, torch.float16 --> Q8_0, shape = {4096, 1024}\n",
"INFO:hf-to-gguf:blk.26.attn_v.weight, torch.float16 --> Q8_0, shape = {4096, 1024}\n",
"INFO:hf-to-gguf:blk.26.attn_output.weight, torch.float16 --> Q8_0, shape = {4096, 4096}\n",
"INFO:hf-to-gguf:blk.26.ffn_gate.weight, torch.float16 --> Q8_0, shape = {4096, 14336}\n",
"INFO:hf-to-gguf:blk.26.ffn_up.weight, torch.float16 --> Q8_0, shape = {4096, 14336}\n",
"INFO:hf-to-gguf:blk.26.ffn_down.weight, torch.float16 --> Q8_0, shape = {14336, 4096}\n",
"INFO:hf-to-gguf:blk.26.attn_norm.weight, torch.float16 --> F32, shape = {4096}\n",
"INFO:hf-to-gguf:blk.26.ffn_norm.weight, torch.float16 --> F32, shape = {4096}\n",
"INFO:hf-to-gguf:blk.27.attn_q.weight, torch.float16 --> Q8_0, shape = {4096, 4096}\n",
"INFO:hf-to-gguf:blk.27.attn_k.weight, torch.float16 --> Q8_0, shape = {4096, 1024}\n",
"INFO:hf-to-gguf:blk.27.attn_v.weight, torch.float16 --> Q8_0, shape = {4096, 1024}\n",
"INFO:hf-to-gguf:blk.27.attn_output.weight, torch.float16 --> Q8_0, shape = {4096, 4096}\n",
"INFO:hf-to-gguf:blk.27.ffn_gate.weight, torch.float16 --> Q8_0, shape = {4096, 14336}\n",
"INFO:hf-to-gguf:blk.27.ffn_up.weight, torch.float16 --> Q8_0, shape = {4096, 14336}\n",
"INFO:hf-to-gguf:blk.27.ffn_down.weight, torch.float16 --> Q8_0, shape = {14336, 4096}\n",
"INFO:hf-to-gguf:blk.27.attn_norm.weight, torch.float16 --> F32, shape = {4096}\n",
"INFO:hf-to-gguf:blk.27.ffn_norm.weight, torch.float16 --> F32, shape = {4096}\n",
"INFO:hf-to-gguf:blk.28.attn_q.weight, torch.float16 --> Q8_0, shape = {4096, 4096}\n",
"INFO:hf-to-gguf:blk.28.attn_k.weight, torch.float16 --> Q8_0, shape = {4096, 1024}\n",
"INFO:hf-to-gguf:blk.28.attn_v.weight, torch.float16 --> Q8_0, shape = {4096, 1024}\n",
"INFO:hf-to-gguf:blk.28.attn_output.weight, torch.float16 --> Q8_0, shape = {4096, 4096}\n",
"INFO:hf-to-gguf:blk.28.ffn_gate.weight, torch.float16 --> Q8_0, shape = {4096, 14336}\n",
"INFO:hf-to-gguf:blk.28.ffn_up.weight, torch.float16 --> Q8_0, shape = {4096, 14336}\n",
"INFO:hf-to-gguf:blk.28.ffn_down.weight, torch.float16 --> Q8_0, shape = {14336, 4096}\n",
"INFO:hf-to-gguf:blk.28.attn_norm.weight, torch.float16 --> F32, shape = {4096}\n",
"INFO:hf-to-gguf:blk.28.ffn_norm.weight, torch.float16 --> F32, shape = {4096}\n",
"INFO:hf-to-gguf:blk.29.attn_q.weight, torch.float16 --> Q8_0, shape = {4096, 4096}\n",
"INFO:hf-to-gguf:blk.29.attn_k.weight, torch.float16 --> Q8_0, shape = {4096, 1024}\n",
"INFO:hf-to-gguf:blk.29.attn_v.weight, torch.float16 --> Q8_0, shape = {4096, 1024}\n",
"INFO:hf-to-gguf:blk.29.attn_output.weight, torch.float16 --> Q8_0, shape = {4096, 4096}\n",
"INFO:hf-to-gguf:blk.29.ffn_gate.weight, torch.float16 --> Q8_0, shape = {4096, 14336}\n",
"INFO:hf-to-gguf:blk.29.ffn_up.weight, torch.float16 --> Q8_0, shape = {4096, 14336}\n",
"INFO:hf-to-gguf:blk.29.ffn_down.weight, torch.float16 --> Q8_0, shape = {14336, 4096}\n",
"INFO:hf-to-gguf:blk.29.attn_norm.weight, torch.float16 --> F32, shape = {4096}\n",
"INFO:hf-to-gguf:blk.29.ffn_norm.weight, torch.float16 --> F32, shape = {4096}\n",
"INFO:hf-to-gguf:blk.30.attn_q.weight, torch.float16 --> Q8_0, shape = {4096, 4096}\n",
"INFO:hf-to-gguf:blk.30.attn_k.weight, torch.float16 --> Q8_0, shape = {4096, 1024}\n",
"INFO:hf-to-gguf:blk.30.attn_v.weight, torch.float16 --> Q8_0, shape = {4096, 1024}\n",
"INFO:hf-to-gguf:blk.30.attn_output.weight, torch.float16 --> Q8_0, shape = {4096, 4096}\n",
"INFO:hf-to-gguf:blk.30.ffn_gate.weight, torch.float16 --> Q8_0, shape = {4096, 14336}\n",
"INFO:hf-to-gguf:blk.30.ffn_up.weight, torch.float16 --> Q8_0, shape = {4096, 14336}\n",
"INFO:hf-to-gguf:blk.30.ffn_down.weight, torch.float16 --> Q8_0, shape = {14336, 4096}\n",
"INFO:hf-to-gguf:blk.30.attn_norm.weight, torch.float16 --> F32, shape = {4096}\n",
"INFO:hf-to-gguf:blk.30.ffn_norm.weight, torch.float16 --> F32, shape = {4096}\n",
"INFO:hf-to-gguf:blk.31.attn_q.weight, torch.float16 --> Q8_0, shape = {4096, 4096}\n",
"INFO:hf-to-gguf:blk.31.attn_k.weight, torch.float16 --> Q8_0, shape = {4096, 1024}\n",
"INFO:hf-to-gguf:blk.31.attn_v.weight, torch.float16 --> Q8_0, shape = {4096, 1024}\n",
"INFO:hf-to-gguf:blk.31.attn_output.weight, torch.float16 --> Q8_0, shape = {4096, 4096}\n",
"INFO:hf-to-gguf:blk.31.ffn_gate.weight, torch.float16 --> Q8_0, shape = {4096, 14336}\n",
"INFO:hf-to-gguf:blk.31.ffn_up.weight, torch.float16 --> Q8_0, shape = {4096, 14336}\n",
"INFO:hf-to-gguf:blk.31.ffn_down.weight, torch.float16 --> Q8_0, shape = {14336, 4096}\n",
"INFO:hf-to-gguf:blk.31.attn_norm.weight, torch.float16 --> F32, shape = {4096}\n",
"INFO:hf-to-gguf:blk.31.ffn_norm.weight, torch.float16 --> F32, shape = {4096}\n",
"INFO:hf-to-gguf:output_norm.weight, torch.float16 --> F32, shape = {4096}\n",
"INFO:hf-to-gguf:output.weight, torch.float16 --> Q8_0, shape = {4096, 32768}\n",
"INFO:hf-to-gguf:Set meta model\n",
"INFO:hf-to-gguf:Set model parameters\n",
"INFO:hf-to-gguf:gguf: context length = 32768\n",
"INFO:hf-to-gguf:gguf: embedding length = 4096\n",
"INFO:hf-to-gguf:gguf: feed forward length = 14336\n",
"INFO:hf-to-gguf:gguf: head count = 32\n",
"INFO:hf-to-gguf:gguf: key-value head count = 8\n",
"INFO:hf-to-gguf:gguf: rope theta = 1000000.0\n",
"INFO:hf-to-gguf:gguf: rms norm epsilon = 1e-05\n",
"INFO:hf-to-gguf:gguf: file type = 7\n",
"INFO:hf-to-gguf:Set model tokenizer\n",
"INFO:gguf.vocab:Setting special token type bos to 1\n",
"INFO:gguf.vocab:Setting special token type eos to 2\n",
"INFO:gguf.vocab:Setting special token type unk to 0\n",
"INFO:gguf.vocab:Setting special token type pad to 770\n",
"INFO:gguf.vocab:Setting add_bos_token to True\n",
"INFO:gguf.vocab:Setting add_eos_token to False\n",
"INFO:hf-to-gguf:Set model quantization version\n",
"INFO:gguf.gguf_writer:Writing the following files:\n",
"INFO:gguf.gguf_writer:/content/vaugheu/MistralBangla3v7b/unsloth.Q8_0.gguf: n_tensors = 291, total_size = 7.7G\n",
"Writing: 100%|██████████| 7.70G/7.70G [03:14<00:00, 39.6Mbyte/s]\n",
"INFO:hf-to-gguf:Model successfully exported to /content/vaugheu/MistralBangla3v7b/unsloth.Q8_0.gguf\n",
"Unsloth: Conversion completed! Output location: /content/vaugheu/MistralBangla3v7b/unsloth.Q8_0.gguf\n",
"Unsloth: Uploading GGUF to Huggingface Hub...\n"
]
},
{
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "9b1d1d58b37f4c0d8d43cd0bfe013238",
"version_major": 2,
"version_minor": 0
},
"text/plain": [
" 0%| | 0/1 [00:00, ?it/s]"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "6ded895c12da47c89d0238e8ee66d11a",
"version_major": 2,
"version_minor": 0
},
"text/plain": [
"unsloth.Q8_0.gguf: 0%| | 0.00/7.70G [00:00, ?B/s]"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Saved GGUF to https://huggingface.co./vaugheu/MistralBangla3v7b\n"
]
}
],
"source": [
"# Save to 8bit Q8_0\n",
"if True: model.save_pretrained_gguf(\"model\", tokenizer,)\n",
"# Remember to go to https://huggingface.co./settings/tokens for a token!\n",
"# And change hf to your username!\n",
"if True: model.push_to_hub_gguf(\"vaugheu/MistralBangla3v7b\", tokenizer, token = \"hf_\")\n",
"\n",
"# Save to 16bit GGUF\n",
"if False: model.save_pretrained_gguf(\"model\", tokenizer, quantization_method = \"f16\")\n",
"if False: model.push_to_hub_gguf(\"vaugheu/MistralBangla3v7b\", tokenizer, quantization_method = \"f16\", token = \"\")\n",
"\n",
"# Save to q4_k_m GGUF\n",
"if False: model.save_pretrained_gguf(\"model\", tokenizer, quantization_method = \"q4_k_m\")\n",
"if False: model.push_to_hub_gguf(\"vaugheu/MistralBangla3v7b\", tokenizer, quantization_method = \"q4_k_m\", token = \"\")\n",
"\n",
"# Save to multiple GGUF options - much faster if you want multiple!\n",
"if False:\n",
" model.push_to_hub_gguf(\n",
" \"vaugheu/MistralBangla3v7b\", # Change hf to your username!\n",
" tokenizer,\n",
" quantization_method = [\"q4_k_m\", \"q8_0\", \"q5_k_m\",],\n",
" token = \"\", # Get a token at https://huggingface.co./settings/tokens\n",
" )"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "bDp0zNpwe6U_"
},
"source": [
"Now, use the `model-unsloth.gguf` file or `model-unsloth-Q4_K_M.gguf` file in `llama.cpp` or a UI based system like `GPT4All`. You can install GPT4All by going [here](https://gpt4all.io/index.html).\n",
"\n",
"**[NEW] Try 2x faster inference in a free Colab for Llama-3.1 8b Instruct [here](https://colab.research.google.com/drive/1T-YBVfnphoVc8E2E854qF3jdia2Ll2W2?usp=sharing)**"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "Zt9CHJqO6p30"
},
"source": [
"And we're done! If you have any questions on Unsloth, we have a [Discord](https://discord.gg/u54VK8m8tk) channel! If you find any bugs or want to keep updated with the latest LLM stuff, or need help, join projects etc, feel free to join our Discord!\n",
"\n",
"Some other links:\n",
"1. Zephyr DPO 2x faster [free Colab](https://colab.research.google.com/drive/15vttTpzzVXv_tJwEk-hIcQ0S9FcEWvwP?usp=sharing)\n",
"2. Llama 7b 2x faster [free Colab](https://colab.research.google.com/drive/1lBzz5KeZJKXjvivbYvmGarix9Ao6Wxe5?usp=sharing)\n",
"3. TinyLlama 4x faster full Alpaca 52K in 1 hour [free Colab](https://colab.research.google.com/drive/1AZghoNBQaMDgWJpi4RbffGM1h6raLUj9?usp=sharing)\n",
"4. CodeLlama 34b 2x faster [A100 on Colab](https://colab.research.google.com/drive/1y7A0AxE3y8gdj4AVkl2aZX47Xu3P1wJT?usp=sharing)\n",
"5. Mistral 7b [free Kaggle version](https://www.kaggle.com/code/danielhanchen/kaggle-mistral-7b-unsloth-notebook)\n",
"6. We also did a [blog](https://huggingface.co./blog/unsloth-trl) with 🤗 HuggingFace, and we're in the TRL [docs](https://huggingface.co./docs/trl/main/en/sft_trainer#accelerate-fine-tuning-2x-using-unsloth)!\n",
"7. `ChatML` for ShareGPT datasets, [conversational notebook](https://colab.research.google.com/drive/1Aau3lgPzeZKQ-98h69CCu1UJcvIBLmy2?usp=sharing)\n",
"8. Text completions like novel writing [notebook](https://colab.research.google.com/drive/1ef-tab5bhkvWmBOObepl1WgJvfvSzn5Q?usp=sharing)\n",
"9. [**NEW**] We make Phi-3 Medium / Mini **2x faster**! See our [Phi-3 Medium notebook](https://colab.research.google.com/drive/1hhdhBa1j_hsymiW9m-WzxQtgqTH_NHqi?usp=sharing)\n",
"10. [**NEW**] We make Gemma-2 9b / 27b **2x faster**! See our [Gemma-2 9b notebook](https://colab.research.google.com/drive/1vIrqH5uYDQwsJ4-OO3DErvuv4pBgVwk4?usp=sharing)\n",
"11. [**NEW**] To finetune and auto export to Ollama, try our [Ollama notebook](https://colab.research.google.com/drive/1WZDi7APtQ9VsvOrQSSC5DDtxq159j8iZ?usp=sharing)\n",
"12. [**NEW**] We make Mistral NeMo 12B 2x faster and fit in under 12GB of VRAM! [Mistral NeMo notebook](https://colab.research.google.com/drive/17d3U-CAIwzmbDRqbZ9NnpHxCkmXB6LZ0?usp=sharing)\n",
"\n",
""
]
}
],
"metadata": {
"accelerator": "GPU",
"colab": {
"gpuType": "T4",
"provenance": []
},
"kernelspec": {
"display_name": "Python 3",
"name": "python3"
},
"language_info": {
"name": "python"
},
"widgets": {
"application/vnd.jupyter.widget-state+json": {
"02426c5157ef4c92b1f912a2078032d6": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "HTMLModel",
"state": {
"_dom_classes": [],
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "HTMLModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/controls",
"_view_module_version": "1.5.0",
"_view_name": "HTMLView",
"description": "",
"description_tooltip": null,
"layout": "IPY_MODEL_13ee10ac59fb4401adb269038138e1d6",
"placeholder": "",
"style": "IPY_MODEL_bff66c38b69e4641865a4cbb532f47c1",
"value": "README.md: 100%"
}
},
"025890c6531d450b9ad67861cff5eb66": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "DescriptionStyleModel",
"state": {
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "DescriptionStyleModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "StyleView",
"description_width": ""
}
},
"0301b3c2076c4e158e8f5af6ce74df77": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "DescriptionStyleModel",
"state": {
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "DescriptionStyleModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "StyleView",
"description_width": ""
}
},
"04405d46d02d4d9d9cafcd1a47f18b19": {
"model_module": "@jupyter-widgets/base",
"model_module_version": "1.2.0",
"model_name": "LayoutModel",
"state": {
"_model_module": "@jupyter-widgets/base",
"_model_module_version": "1.2.0",
"_model_name": "LayoutModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "LayoutView",
"align_content": null,
"align_items": null,
"align_self": null,
"border": null,
"bottom": null,
"display": null,
"flex": null,
"flex_flow": null,
"grid_area": null,
"grid_auto_columns": null,
"grid_auto_flow": null,
"grid_auto_rows": null,
"grid_column": null,
"grid_gap": null,
"grid_row": null,
"grid_template_areas": null,
"grid_template_columns": null,
"grid_template_rows": null,
"height": null,
"justify_content": null,
"justify_items": null,
"left": null,
"margin": null,
"max_height": null,
"max_width": null,
"min_height": null,
"min_width": null,
"object_fit": null,
"object_position": null,
"order": null,
"overflow": null,
"overflow_x": null,
"overflow_y": null,
"padding": null,
"right": null,
"top": null,
"visibility": null,
"width": null
}
},
"07f800e8119b48f8b51dff9f48397810": {
"model_module": "@jupyter-widgets/base",
"model_module_version": "1.2.0",
"model_name": "LayoutModel",
"state": {
"_model_module": "@jupyter-widgets/base",
"_model_module_version": "1.2.0",
"_model_name": "LayoutModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "LayoutView",
"align_content": null,
"align_items": null,
"align_self": null,
"border": null,
"bottom": null,
"display": null,
"flex": null,
"flex_flow": null,
"grid_area": null,
"grid_auto_columns": null,
"grid_auto_flow": null,
"grid_auto_rows": null,
"grid_column": null,
"grid_gap": null,
"grid_row": null,
"grid_template_areas": null,
"grid_template_columns": null,
"grid_template_rows": null,
"height": null,
"justify_content": null,
"justify_items": null,
"left": null,
"margin": null,
"max_height": null,
"max_width": null,
"min_height": null,
"min_width": null,
"object_fit": null,
"object_position": null,
"order": null,
"overflow": null,
"overflow_x": null,
"overflow_y": null,
"padding": null,
"right": null,
"top": null,
"visibility": null,
"width": null
}
},
"0994869c36a4402fa6bb0391c28027e0": {
"model_module": "@jupyter-widgets/base",
"model_module_version": "1.2.0",
"model_name": "LayoutModel",
"state": {
"_model_module": "@jupyter-widgets/base",
"_model_module_version": "1.2.0",
"_model_name": "LayoutModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "LayoutView",
"align_content": null,
"align_items": null,
"align_self": null,
"border": null,
"bottom": null,
"display": null,
"flex": null,
"flex_flow": null,
"grid_area": null,
"grid_auto_columns": null,
"grid_auto_flow": null,
"grid_auto_rows": null,
"grid_column": null,
"grid_gap": null,
"grid_row": null,
"grid_template_areas": null,
"grid_template_columns": null,
"grid_template_rows": null,
"height": null,
"justify_content": null,
"justify_items": null,
"left": null,
"margin": null,
"max_height": null,
"max_width": null,
"min_height": null,
"min_width": null,
"object_fit": null,
"object_position": null,
"order": null,
"overflow": null,
"overflow_x": null,
"overflow_y": null,
"padding": null,
"right": null,
"top": null,
"visibility": null,
"width": null
}
},
"0d91e0c88db442e9a5f74d66c75fe33a": {
"model_module": "@jupyter-widgets/base",
"model_module_version": "1.2.0",
"model_name": "LayoutModel",
"state": {
"_model_module": "@jupyter-widgets/base",
"_model_module_version": "1.2.0",
"_model_name": "LayoutModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "LayoutView",
"align_content": null,
"align_items": null,
"align_self": null,
"border": null,
"bottom": null,
"display": null,
"flex": null,
"flex_flow": null,
"grid_area": null,
"grid_auto_columns": null,
"grid_auto_flow": null,
"grid_auto_rows": null,
"grid_column": null,
"grid_gap": null,
"grid_row": null,
"grid_template_areas": null,
"grid_template_columns": null,
"grid_template_rows": null,
"height": null,
"justify_content": null,
"justify_items": null,
"left": null,
"margin": null,
"max_height": null,
"max_width": null,
"min_height": null,
"min_width": null,
"object_fit": null,
"object_position": null,
"order": null,
"overflow": null,
"overflow_x": null,
"overflow_y": null,
"padding": null,
"right": null,
"top": null,
"visibility": null,
"width": null
}
},
"0e8b4643c42a462d90cbddd169fbb17b": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "HTMLModel",
"state": {
"_dom_classes": [],
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "HTMLModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/controls",
"_view_module_version": "1.5.0",
"_view_name": "HTMLView",
"description": "",
"description_tooltip": null,
"layout": "IPY_MODEL_bcfa0a1a0022496e850f1d44cac0532b",
"placeholder": "",
"style": "IPY_MODEL_391cef2e49a74c94bf484fda4b413b2b",
"value": "100%"
}
},
"13858c39f00043eab784b43e78f75e96": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "DescriptionStyleModel",
"state": {
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "DescriptionStyleModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "StyleView",
"description_width": ""
}
},
"13ee10ac59fb4401adb269038138e1d6": {
"model_module": "@jupyter-widgets/base",
"model_module_version": "1.2.0",
"model_name": "LayoutModel",
"state": {
"_model_module": "@jupyter-widgets/base",
"_model_module_version": "1.2.0",
"_model_name": "LayoutModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "LayoutView",
"align_content": null,
"align_items": null,
"align_self": null,
"border": null,
"bottom": null,
"display": null,
"flex": null,
"flex_flow": null,
"grid_area": null,
"grid_auto_columns": null,
"grid_auto_flow": null,
"grid_auto_rows": null,
"grid_column": null,
"grid_gap": null,
"grid_row": null,
"grid_template_areas": null,
"grid_template_columns": null,
"grid_template_rows": null,
"height": null,
"justify_content": null,
"justify_items": null,
"left": null,
"margin": null,
"max_height": null,
"max_width": null,
"min_height": null,
"min_width": null,
"object_fit": null,
"object_position": null,
"order": null,
"overflow": null,
"overflow_x": null,
"overflow_y": null,
"padding": null,
"right": null,
"top": null,
"visibility": null,
"width": null
}
},
"1480812645954012a9dc22049f1295a5": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "HTMLModel",
"state": {
"_dom_classes": [],
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "HTMLModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/controls",
"_view_module_version": "1.5.0",
"_view_name": "HTMLView",
"description": "",
"description_tooltip": null,
"layout": "IPY_MODEL_7943696966dd4434900e30aed33fafda",
"placeholder": "",
"style": "IPY_MODEL_542a9b28ae904946a6fbbb57d1815e07",
"value": " 446/446 [00:00<00:00, 32.6kB/s]"
}
},
"161c263284df4f68a4358e4452dbef3a": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "FloatProgressModel",
"state": {
"_dom_classes": [],
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "FloatProgressModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/controls",
"_view_module_version": "1.5.0",
"_view_name": "ProgressView",
"bar_style": "success",
"description": "",
"description_tooltip": null,
"layout": "IPY_MODEL_07f800e8119b48f8b51dff9f48397810",
"max": 587404,
"min": 0,
"orientation": "horizontal",
"style": "IPY_MODEL_1eae97f1eef448a28334a0055482204e",
"value": 587404
}
},
"168b4bc0ddd548cc8e3632eee17f6333": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "FloatProgressModel",
"state": {
"_dom_classes": [],
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "FloatProgressModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/controls",
"_view_module_version": "1.5.0",
"_view_name": "ProgressView",
"bar_style": "success",
"description": "",
"description_tooltip": null,
"layout": "IPY_MODEL_8657ee65ecd84d5a9060532e3120ebc2",
"max": 157,
"min": 0,
"orientation": "horizontal",
"style": "IPY_MODEL_27c682c7ccd54f4e90597cbeff916f5b",
"value": 157
}
},
"16f2c1312876443784df678b0fe424b1": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "FloatProgressModel",
"state": {
"_dom_classes": [],
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "FloatProgressModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/controls",
"_view_module_version": "1.5.0",
"_view_name": "ProgressView",
"bar_style": "success",
"description": "",
"description_tooltip": null,
"layout": "IPY_MODEL_d75e04ea7c4644a3a3390b98284eb71e",
"max": 446,
"min": 0,
"orientation": "horizontal",
"style": "IPY_MODEL_9f7cf13438a84bb29002d4dcf9583fd4",
"value": 446
}
},
"1703f1e2cede4393bdc5576aa28d8d26": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "HTMLModel",
"state": {
"_dom_classes": [],
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "HTMLModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/controls",
"_view_module_version": "1.5.0",
"_view_name": "HTMLView",
"description": "",
"description_tooltip": null,
"layout": "IPY_MODEL_3f88168116bf490297e5e8fa0cd31796",
"placeholder": "",
"style": "IPY_MODEL_5ac8c654086747a6850b6462ccee2c35",
"value": " 176M/? [00:03<00:00, 78.1MB/s]"
}
},
"17b0a9fada8c402f90f7ab8ac3f84006": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "HTMLModel",
"state": {
"_dom_classes": [],
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "HTMLModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/controls",
"_view_module_version": "1.5.0",
"_view_name": "HTMLView",
"description": "",
"description_tooltip": null,
"layout": "IPY_MODEL_af4415d6ed8e4f149cbe55ad78640a8e",
"placeholder": "",
"style": "IPY_MODEL_30983f8961bf4d83aacb77139690ed63",
"value": " 588/588 [00:00<00:00, 47.0kB/s]"
}
},
"17e3bbf2df974aa1b840e4511ed76afd": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "FloatProgressModel",
"state": {
"_dom_classes": [],
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "FloatProgressModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/controls",
"_view_module_version": "1.5.0",
"_view_name": "ProgressView",
"bar_style": "success",
"description": "",
"description_tooltip": null,
"layout": "IPY_MODEL_4562d6548a394508b6a86dd9fd2cb7ca",
"max": 172026,
"min": 0,
"orientation": "horizontal",
"style": "IPY_MODEL_8057d60eab0843d1bcb06ff794b911aa",
"value": 172026
}
},
"1a4e9b55836f42cfbb36fc4f0a01252c": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "DescriptionStyleModel",
"state": {
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "DescriptionStyleModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "StyleView",
"description_width": ""
}
},
"1b5347ed1b584555b82fe2e064595c67": {
"model_module": "@jupyter-widgets/base",
"model_module_version": "1.2.0",
"model_name": "LayoutModel",
"state": {
"_model_module": "@jupyter-widgets/base",
"_model_module_version": "1.2.0",
"_model_name": "LayoutModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "LayoutView",
"align_content": null,
"align_items": null,
"align_self": null,
"border": null,
"bottom": null,
"display": null,
"flex": null,
"flex_flow": null,
"grid_area": null,
"grid_auto_columns": null,
"grid_auto_flow": null,
"grid_auto_rows": null,
"grid_column": null,
"grid_gap": null,
"grid_row": null,
"grid_template_areas": null,
"grid_template_columns": null,
"grid_template_rows": null,
"height": null,
"justify_content": null,
"justify_items": null,
"left": null,
"margin": null,
"max_height": null,
"max_width": null,
"min_height": null,
"min_width": null,
"object_fit": null,
"object_position": null,
"order": null,
"overflow": null,
"overflow_x": null,
"overflow_y": null,
"padding": null,
"right": null,
"top": null,
"visibility": null,
"width": null
}
},
"1eae97f1eef448a28334a0055482204e": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "ProgressStyleModel",
"state": {
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "ProgressStyleModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "StyleView",
"bar_color": null,
"description_width": ""
}
},
"232edccc247f40afb3aaf4458a45c084": {
"model_module": "@jupyter-widgets/base",
"model_module_version": "1.2.0",
"model_name": "LayoutModel",
"state": {
"_model_module": "@jupyter-widgets/base",
"_model_module_version": "1.2.0",
"_model_name": "LayoutModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "LayoutView",
"align_content": null,
"align_items": null,
"align_self": null,
"border": null,
"bottom": null,
"display": null,
"flex": null,
"flex_flow": null,
"grid_area": null,
"grid_auto_columns": null,
"grid_auto_flow": null,
"grid_auto_rows": null,
"grid_column": null,
"grid_gap": null,
"grid_row": null,
"grid_template_areas": null,
"grid_template_columns": null,
"grid_template_rows": null,
"height": null,
"justify_content": null,
"justify_items": null,
"left": null,
"margin": null,
"max_height": null,
"max_width": null,
"min_height": null,
"min_width": null,
"object_fit": null,
"object_position": null,
"order": null,
"overflow": null,
"overflow_x": null,
"overflow_y": null,
"padding": null,
"right": null,
"top": null,
"visibility": null,
"width": null
}
},
"233836d2c7b048009a8d5f2039ff0483": {
"model_module": "@jupyter-widgets/base",
"model_module_version": "1.2.0",
"model_name": "LayoutModel",
"state": {
"_model_module": "@jupyter-widgets/base",
"_model_module_version": "1.2.0",
"_model_name": "LayoutModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "LayoutView",
"align_content": null,
"align_items": null,
"align_self": null,
"border": null,
"bottom": null,
"display": null,
"flex": null,
"flex_flow": null,
"grid_area": null,
"grid_auto_columns": null,
"grid_auto_flow": null,
"grid_auto_rows": null,
"grid_column": null,
"grid_gap": null,
"grid_row": null,
"grid_template_areas": null,
"grid_template_columns": null,
"grid_template_rows": null,
"height": null,
"justify_content": null,
"justify_items": null,
"left": null,
"margin": null,
"max_height": null,
"max_width": null,
"min_height": null,
"min_width": null,
"object_fit": null,
"object_position": null,
"order": null,
"overflow": null,
"overflow_x": null,
"overflow_y": null,
"padding": null,
"right": null,
"top": null,
"visibility": null,
"width": null
}
},
"25016ec6a1ff42f893105c6e2abcc587": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "HBoxModel",
"state": {
"_dom_classes": [],
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "HBoxModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/controls",
"_view_module_version": "1.5.0",
"_view_name": "HBoxView",
"box_style": "",
"children": [
"IPY_MODEL_812857d3b17b403f989b3686cd520c02",
"IPY_MODEL_473bd6610c564b8c8ad7a4cfa842979d",
"IPY_MODEL_52081839832a457982c1415013515c97"
],
"layout": "IPY_MODEL_3e568bf542e34c269de58bf11fd360b7"
}
},
"251591a1f67849b59664988d900c9320": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "DescriptionStyleModel",
"state": {
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "DescriptionStyleModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "StyleView",
"description_width": ""
}
},
"252c63f990844e079f30f825d2c07184": {
"model_module": "@jupyter-widgets/base",
"model_module_version": "1.2.0",
"model_name": "LayoutModel",
"state": {
"_model_module": "@jupyter-widgets/base",
"_model_module_version": "1.2.0",
"_model_name": "LayoutModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "LayoutView",
"align_content": null,
"align_items": null,
"align_self": null,
"border": null,
"bottom": null,
"display": null,
"flex": null,
"flex_flow": null,
"grid_area": null,
"grid_auto_columns": null,
"grid_auto_flow": null,
"grid_auto_rows": null,
"grid_column": null,
"grid_gap": null,
"grid_row": null,
"grid_template_areas": null,
"grid_template_columns": null,
"grid_template_rows": null,
"height": null,
"justify_content": null,
"justify_items": null,
"left": null,
"margin": null,
"max_height": null,
"max_width": null,
"min_height": null,
"min_width": null,
"object_fit": null,
"object_position": null,
"order": null,
"overflow": null,
"overflow_x": null,
"overflow_y": null,
"padding": null,
"right": null,
"top": null,
"visibility": null,
"width": null
}
},
"2595d0c6016849d999725fe309b38414": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "ProgressStyleModel",
"state": {
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "ProgressStyleModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "StyleView",
"bar_color": null,
"description_width": ""
}
},
"25fc5fc784a44aa491b841f185ef374d": {
"model_module": "@jupyter-widgets/base",
"model_module_version": "1.2.0",
"model_name": "LayoutModel",
"state": {
"_model_module": "@jupyter-widgets/base",
"_model_module_version": "1.2.0",
"_model_name": "LayoutModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "LayoutView",
"align_content": null,
"align_items": null,
"align_self": null,
"border": null,
"bottom": null,
"display": null,
"flex": null,
"flex_flow": null,
"grid_area": null,
"grid_auto_columns": null,
"grid_auto_flow": null,
"grid_auto_rows": null,
"grid_column": null,
"grid_gap": null,
"grid_row": null,
"grid_template_areas": null,
"grid_template_columns": null,
"grid_template_rows": null,
"height": null,
"justify_content": null,
"justify_items": null,
"left": null,
"margin": null,
"max_height": null,
"max_width": null,
"min_height": null,
"min_width": null,
"object_fit": null,
"object_position": null,
"order": null,
"overflow": null,
"overflow_x": null,
"overflow_y": null,
"padding": null,
"right": null,
"top": null,
"visibility": null,
"width": null
}
},
"268e472f9e5845fc895e167d0513aece": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "DescriptionStyleModel",
"state": {
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "DescriptionStyleModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "StyleView",
"description_width": ""
}
},
"26cb5c9cb78349b2b4e3243752093cc4": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "HTMLModel",
"state": {
"_dom_classes": [],
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "HTMLModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/controls",
"_view_module_version": "1.5.0",
"_view_name": "HTMLView",
"description": "",
"description_tooltip": null,
"layout": "IPY_MODEL_f61217d62cf94257b6cc9673d8e6cab1",
"placeholder": "",
"style": "IPY_MODEL_e26f854045484cd7a78f4df5b2e2bdc5",
"value": "train-00000-of-00002.parquet: 100%"
}
},
"27c682c7ccd54f4e90597cbeff916f5b": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "ProgressStyleModel",
"state": {
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "ProgressStyleModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "StyleView",
"bar_color": null,
"description_width": ""
}
},
"28575a44bd4a4ff4995bef61a1ff923f": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "FloatProgressModel",
"state": {
"_dom_classes": [],
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "FloatProgressModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/controls",
"_view_module_version": "1.5.0",
"_view_name": "ProgressView",
"bar_style": "danger",
"description": "",
"description_tooltip": null,
"layout": "IPY_MODEL_be112d605e874960b57620ab725742c1",
"max": 4138270821,
"min": 0,
"orientation": "horizontal",
"style": "IPY_MODEL_71d2164bd80c4c7ebdba192b545307e0",
"value": 4138270427
}
},
"2db4c72d8b2448ffad721123c1641cc7": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "HTMLModel",
"state": {
"_dom_classes": [],
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "HTMLModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/controls",
"_view_module_version": "1.5.0",
"_view_name": "HTMLView",
"description": "",
"description_tooltip": null,
"layout": "IPY_MODEL_fe84cb01a2fc4803b6959f18b194c476",
"placeholder": "",
"style": "IPY_MODEL_c8509c42f414476e8ff36ca377a9b062",
"value": " 7.71G/? [01:07<00:00, 137MB/s]"
}
},
"2fb10f28bb0a4ed498f37668d890daed": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "ProgressStyleModel",
"state": {
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "ProgressStyleModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "StyleView",
"bar_color": null,
"description_width": ""
}
},
"30983f8961bf4d83aacb77139690ed63": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "DescriptionStyleModel",
"state": {
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "DescriptionStyleModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "StyleView",
"description_width": ""
}
},
"31b710c446a04859bb1bc068b9c42bcc": {
"model_module": "@jupyter-widgets/base",
"model_module_version": "1.2.0",
"model_name": "LayoutModel",
"state": {
"_model_module": "@jupyter-widgets/base",
"_model_module_version": "1.2.0",
"_model_name": "LayoutModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "LayoutView",
"align_content": null,
"align_items": null,
"align_self": null,
"border": null,
"bottom": null,
"display": null,
"flex": null,
"flex_flow": null,
"grid_area": null,
"grid_auto_columns": null,
"grid_auto_flow": null,
"grid_auto_rows": null,
"grid_column": null,
"grid_gap": null,
"grid_row": null,
"grid_template_areas": null,
"grid_template_columns": null,
"grid_template_rows": null,
"height": null,
"justify_content": null,
"justify_items": null,
"left": null,
"margin": null,
"max_height": null,
"max_width": null,
"min_height": null,
"min_width": null,
"object_fit": null,
"object_position": null,
"order": null,
"overflow": null,
"overflow_x": null,
"overflow_y": null,
"padding": null,
"right": null,
"top": null,
"visibility": null,
"width": null
}
},
"34172978ed324047b813e6c42f5d8930": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "ProgressStyleModel",
"state": {
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "ProgressStyleModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "StyleView",
"bar_color": null,
"description_width": ""
}
},
"362a469d210a40c4beb44614d0dff94d": {
"model_module": "@jupyter-widgets/base",
"model_module_version": "1.2.0",
"model_name": "LayoutModel",
"state": {
"_model_module": "@jupyter-widgets/base",
"_model_module_version": "1.2.0",
"_model_name": "LayoutModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "LayoutView",
"align_content": null,
"align_items": null,
"align_self": null,
"border": null,
"bottom": null,
"display": null,
"flex": null,
"flex_flow": null,
"grid_area": null,
"grid_auto_columns": null,
"grid_auto_flow": null,
"grid_auto_rows": null,
"grid_column": null,
"grid_gap": null,
"grid_row": null,
"grid_template_areas": null,
"grid_template_columns": null,
"grid_template_rows": null,
"height": null,
"justify_content": null,
"justify_items": null,
"left": null,
"margin": null,
"max_height": null,
"max_width": null,
"min_height": null,
"min_width": null,
"object_fit": null,
"object_position": null,
"order": null,
"overflow": null,
"overflow_x": null,
"overflow_y": null,
"padding": null,
"right": null,
"top": null,
"visibility": null,
"width": null
}
},
"37aeacc4ed6349b096efc3513d027c53": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "ProgressStyleModel",
"state": {
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "ProgressStyleModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "StyleView",
"bar_color": null,
"description_width": ""
}
},
"38b7d7231e3a4b078ff15c0af7d4bab6": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "HTMLModel",
"state": {
"_dom_classes": [],
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "HTMLModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/controls",
"_view_module_version": "1.5.0",
"_view_name": "HTMLView",
"description": "",
"description_tooltip": null,
"layout": "IPY_MODEL_82c8aca0f1a24c38a2c111dfa85df233",
"placeholder": "",
"style": "IPY_MODEL_9dc305d92ded49e58e76469d67d9a2a7",
"value": "tokenizer.model: 100%"
}
},
"391cef2e49a74c94bf484fda4b413b2b": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "DescriptionStyleModel",
"state": {
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "DescriptionStyleModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "StyleView",
"description_width": ""
}
},
"3b208739190647aba89d38664f3c04ff": {
"model_module": "@jupyter-widgets/base",
"model_module_version": "1.2.0",
"model_name": "LayoutModel",
"state": {
"_model_module": "@jupyter-widgets/base",
"_model_module_version": "1.2.0",
"_model_name": "LayoutModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "LayoutView",
"align_content": null,
"align_items": null,
"align_self": null,
"border": null,
"bottom": null,
"display": null,
"flex": null,
"flex_flow": null,
"grid_area": null,
"grid_auto_columns": null,
"grid_auto_flow": null,
"grid_auto_rows": null,
"grid_column": null,
"grid_gap": null,
"grid_row": null,
"grid_template_areas": null,
"grid_template_columns": null,
"grid_template_rows": null,
"height": null,
"justify_content": null,
"justify_items": null,
"left": null,
"margin": null,
"max_height": null,
"max_width": null,
"min_height": null,
"min_width": null,
"object_fit": null,
"object_position": null,
"order": null,
"overflow": null,
"overflow_x": null,
"overflow_y": null,
"padding": null,
"right": null,
"top": null,
"visibility": null,
"width": null
}
},
"3c9e9bb23c054fc8b9f3a6658e8d5a40": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "ProgressStyleModel",
"state": {
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "ProgressStyleModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "StyleView",
"bar_color": null,
"description_width": ""
}
},
"3cc5e854f9a2462fb4eac1b7bbc26ebb": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "HTMLModel",
"state": {
"_dom_classes": [],
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "HTMLModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/controls",
"_view_module_version": "1.5.0",
"_view_name": "HTMLView",
"description": "",
"description_tooltip": null,
"layout": "IPY_MODEL_4a38b8f3bcd74aa6af1d2d143fc5c1d2",
"placeholder": "",
"style": "IPY_MODEL_5d69c9c0eb454c998628d042720175c2",
"value": " 144M/144M [00:02<00:00, 53.6MB/s]"
}
},
"3e568bf542e34c269de58bf11fd360b7": {
"model_module": "@jupyter-widgets/base",
"model_module_version": "1.2.0",
"model_name": "LayoutModel",
"state": {
"_model_module": "@jupyter-widgets/base",
"_model_module_version": "1.2.0",
"_model_name": "LayoutModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "LayoutView",
"align_content": null,
"align_items": null,
"align_self": null,
"border": null,
"bottom": null,
"display": null,
"flex": null,
"flex_flow": null,
"grid_area": null,
"grid_auto_columns": null,
"grid_auto_flow": null,
"grid_auto_rows": null,
"grid_column": null,
"grid_gap": null,
"grid_row": null,
"grid_template_areas": null,
"grid_template_columns": null,
"grid_template_rows": null,
"height": null,
"justify_content": null,
"justify_items": null,
"left": null,
"margin": null,
"max_height": null,
"max_width": null,
"min_height": null,
"min_width": null,
"object_fit": null,
"object_position": null,
"order": null,
"overflow": null,
"overflow_x": null,
"overflow_y": null,
"padding": null,
"right": null,
"top": null,
"visibility": null,
"width": null
}
},
"3f3b84e262d744558b132ac31da96081": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "FloatProgressModel",
"state": {
"_dom_classes": [],
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "FloatProgressModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/controls",
"_view_module_version": "1.5.0",
"_view_name": "ProgressView",
"bar_style": "success",
"description": "",
"description_tooltip": null,
"layout": "IPY_MODEL_749165aa361b47eda47e778a37176012",
"max": 587404,
"min": 0,
"orientation": "horizontal",
"style": "IPY_MODEL_a4ff849ee64f4acd8296a24d2370a25b",
"value": 587404
}
},
"3f47030858274683b8b14ad06cc8c0d5": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "HTMLModel",
"state": {
"_dom_classes": [],
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "HTMLModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/controls",
"_view_module_version": "1.5.0",
"_view_name": "HTMLView",
"description": "",
"description_tooltip": null,
"layout": "IPY_MODEL_c5e622547fb048128d67240d16152f79",
"placeholder": "",
"style": "IPY_MODEL_251591a1f67849b59664988d900c9320",
"value": " 1.96M/1.96M [00:00<00:00, 3.02MB/s]"
}
},
"3f88168116bf490297e5e8fa0cd31796": {
"model_module": "@jupyter-widgets/base",
"model_module_version": "1.2.0",
"model_name": "LayoutModel",
"state": {
"_model_module": "@jupyter-widgets/base",
"_model_module_version": "1.2.0",
"_model_name": "LayoutModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "LayoutView",
"align_content": null,
"align_items": null,
"align_self": null,
"border": null,
"bottom": null,
"display": null,
"flex": null,
"flex_flow": null,
"grid_area": null,
"grid_auto_columns": null,
"grid_auto_flow": null,
"grid_auto_rows": null,
"grid_column": null,
"grid_gap": null,
"grid_row": null,
"grid_template_areas": null,
"grid_template_columns": null,
"grid_template_rows": null,
"height": null,
"justify_content": null,
"justify_items": null,
"left": null,
"margin": null,
"max_height": null,
"max_width": null,
"min_height": null,
"min_width": null,
"object_fit": null,
"object_position": null,
"order": null,
"overflow": null,
"overflow_x": null,
"overflow_y": null,
"padding": null,
"right": null,
"top": null,
"visibility": null,
"width": null
}
},
"406e55d150d54f9db3f324e487e3aae9": {
"model_module": "@jupyter-widgets/base",
"model_module_version": "1.2.0",
"model_name": "LayoutModel",
"state": {
"_model_module": "@jupyter-widgets/base",
"_model_module_version": "1.2.0",
"_model_name": "LayoutModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "LayoutView",
"align_content": null,
"align_items": null,
"align_self": null,
"border": null,
"bottom": null,
"display": null,
"flex": null,
"flex_flow": null,
"grid_area": null,
"grid_auto_columns": null,
"grid_auto_flow": null,
"grid_auto_rows": null,
"grid_column": null,
"grid_gap": null,
"grid_row": null,
"grid_template_areas": null,
"grid_template_columns": null,
"grid_template_rows": null,
"height": null,
"justify_content": null,
"justify_items": null,
"left": null,
"margin": null,
"max_height": null,
"max_width": null,
"min_height": null,
"min_width": null,
"object_fit": null,
"object_position": null,
"order": null,
"overflow": null,
"overflow_x": null,
"overflow_y": null,
"padding": null,
"right": null,
"top": null,
"visibility": null,
"width": null
}
},
"429d057b1f4b46b1a59deff19df8c51f": {
"model_module": "@jupyter-widgets/base",
"model_module_version": "1.2.0",
"model_name": "LayoutModel",
"state": {
"_model_module": "@jupyter-widgets/base",
"_model_module_version": "1.2.0",
"_model_name": "LayoutModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "LayoutView",
"align_content": null,
"align_items": null,
"align_self": null,
"border": null,
"bottom": null,
"display": null,
"flex": null,
"flex_flow": null,
"grid_area": null,
"grid_auto_columns": null,
"grid_auto_flow": null,
"grid_auto_rows": null,
"grid_column": null,
"grid_gap": null,
"grid_row": null,
"grid_template_areas": null,
"grid_template_columns": null,
"grid_template_rows": null,
"height": null,
"justify_content": null,
"justify_items": null,
"left": null,
"margin": null,
"max_height": null,
"max_width": null,
"min_height": null,
"min_width": null,
"object_fit": null,
"object_position": null,
"order": null,
"overflow": null,
"overflow_x": null,
"overflow_y": null,
"padding": null,
"right": null,
"top": null,
"visibility": null,
"width": null
}
},
"4562d6548a394508b6a86dd9fd2cb7ca": {
"model_module": "@jupyter-widgets/base",
"model_module_version": "1.2.0",
"model_name": "LayoutModel",
"state": {
"_model_module": "@jupyter-widgets/base",
"_model_module_version": "1.2.0",
"_model_name": "LayoutModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "LayoutView",
"align_content": null,
"align_items": null,
"align_self": null,
"border": null,
"bottom": null,
"display": null,
"flex": null,
"flex_flow": null,
"grid_area": null,
"grid_auto_columns": null,
"grid_auto_flow": null,
"grid_auto_rows": null,
"grid_column": null,
"grid_gap": null,
"grid_row": null,
"grid_template_areas": null,
"grid_template_columns": null,
"grid_template_rows": null,
"height": null,
"justify_content": null,
"justify_items": null,
"left": null,
"margin": null,
"max_height": null,
"max_width": null,
"min_height": null,
"min_width": null,
"object_fit": null,
"object_position": null,
"order": null,
"overflow": null,
"overflow_x": null,
"overflow_y": null,
"padding": null,
"right": null,
"top": null,
"visibility": null,
"width": null
}
},
"4664916ffbe54f33adbf1b416fd5f384": {
"model_module": "@jupyter-widgets/base",
"model_module_version": "1.2.0",
"model_name": "LayoutModel",
"state": {
"_model_module": "@jupyter-widgets/base",
"_model_module_version": "1.2.0",
"_model_name": "LayoutModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "LayoutView",
"align_content": null,
"align_items": null,
"align_self": null,
"border": null,
"bottom": null,
"display": null,
"flex": null,
"flex_flow": null,
"grid_area": null,
"grid_auto_columns": null,
"grid_auto_flow": null,
"grid_auto_rows": null,
"grid_column": null,
"grid_gap": null,
"grid_row": null,
"grid_template_areas": null,
"grid_template_columns": null,
"grid_template_rows": null,
"height": null,
"justify_content": null,
"justify_items": null,
"left": null,
"margin": null,
"max_height": null,
"max_width": null,
"min_height": null,
"min_width": null,
"object_fit": null,
"object_position": null,
"order": null,
"overflow": null,
"overflow_x": null,
"overflow_y": null,
"padding": null,
"right": null,
"top": null,
"visibility": null,
"width": null
}
},
"467cef144dbd4d99bb1f5111c8ca25fa": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "DescriptionStyleModel",
"state": {
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "DescriptionStyleModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "StyleView",
"description_width": ""
}
},
"473bd6610c564b8c8ad7a4cfa842979d": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "FloatProgressModel",
"state": {
"_dom_classes": [],
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "FloatProgressModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/controls",
"_view_module_version": "1.5.0",
"_view_name": "ProgressView",
"bar_style": "success",
"description": "",
"description_tooltip": null,
"layout": "IPY_MODEL_9e51e029a44145c4ab2572cf91841696",
"max": 1,
"min": 0,
"orientation": "horizontal",
"style": "IPY_MODEL_2fb10f28bb0a4ed498f37668d890daed",
"value": 1
}
},
"48aeec0877b54f7bab9cdb19e5792d6b": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "FloatProgressModel",
"state": {
"_dom_classes": [],
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "FloatProgressModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/controls",
"_view_module_version": "1.5.0",
"_view_name": "ProgressView",
"bar_style": "success",
"description": "",
"description_tooltip": null,
"layout": "IPY_MODEL_843bc72177104b4782b95cb2f741129a",
"max": 1,
"min": 0,
"orientation": "horizontal",
"style": "IPY_MODEL_e13f629d29b0413985598507411192a3",
"value": 1
}
},
"4962b782c5ca4670af98825a3438ac13": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "HTMLModel",
"state": {
"_dom_classes": [],
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "HTMLModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/controls",
"_view_module_version": "1.5.0",
"_view_name": "HTMLView",
"description": "",
"description_tooltip": null,
"layout": "IPY_MODEL_79d52fabb462442a97f443c6b361f213",
"placeholder": "",
"style": "IPY_MODEL_bc13c65b38ed4653ab3f9a99d861f4dc",
"value": "unsloth.Q8_0.gguf: "
}
},
"4a38b8f3bcd74aa6af1d2d143fc5c1d2": {
"model_module": "@jupyter-widgets/base",
"model_module_version": "1.2.0",
"model_name": "LayoutModel",
"state": {
"_model_module": "@jupyter-widgets/base",
"_model_module_version": "1.2.0",
"_model_name": "LayoutModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "LayoutView",
"align_content": null,
"align_items": null,
"align_self": null,
"border": null,
"bottom": null,
"display": null,
"flex": null,
"flex_flow": null,
"grid_area": null,
"grid_auto_columns": null,
"grid_auto_flow": null,
"grid_auto_rows": null,
"grid_column": null,
"grid_gap": null,
"grid_row": null,
"grid_template_areas": null,
"grid_template_columns": null,
"grid_template_rows": null,
"height": null,
"justify_content": null,
"justify_items": null,
"left": null,
"margin": null,
"max_height": null,
"max_width": null,
"min_height": null,
"min_width": null,
"object_fit": null,
"object_position": null,
"order": null,
"overflow": null,
"overflow_x": null,
"overflow_y": null,
"padding": null,
"right": null,
"top": null,
"visibility": null,
"width": null
}
},
"4abd679e38dc4be09425ce126264175e": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "HBoxModel",
"state": {
"_dom_classes": [],
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "HBoxModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/controls",
"_view_module_version": "1.5.0",
"_view_name": "HBoxView",
"box_style": "",
"children": [
"IPY_MODEL_a1d2719d076145d8a88e101a53937596",
"IPY_MODEL_161c263284df4f68a4358e4452dbef3a",
"IPY_MODEL_f288ceb6bc954b9cab4113f679266350"
],
"layout": "IPY_MODEL_66996de2024046ff9801f1d36859098c"
}
},
"4c00184bff2b4f61a8b2b0866948bab0": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "HTMLModel",
"state": {
"_dom_classes": [],
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "HTMLModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/controls",
"_view_module_version": "1.5.0",
"_view_name": "HTMLView",
"description": "",
"description_tooltip": null,
"layout": "IPY_MODEL_e9755d20f6cb4674b0bc6adb6da5015d",
"placeholder": "",
"style": "IPY_MODEL_a1f1649939a64ae6980283dece79934b",
"value": " 172026/172026 [00:11<00:00, 19563.69 examples/s]"
}
},
"4db8741fb5334720b19a134b0686eaea": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "DescriptionStyleModel",
"state": {
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "DescriptionStyleModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "StyleView",
"description_width": ""
}
},
"4f98983f315f498981f5aa4de015076e": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "HTMLModel",
"state": {
"_dom_classes": [],
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "HTMLModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/controls",
"_view_module_version": "1.5.0",
"_view_name": "HTMLView",
"description": "",
"description_tooltip": null,
"layout": "IPY_MODEL_bd47b355ee6b45b681d0a03162e0872e",
"placeholder": "",
"style": "IPY_MODEL_b7b47d22e60b4f70bcab335bccc016f7",
"value": " 1/1 [00:01<00:00, 1.64s/it]"
}
},
"4fb5a1222abd43c885f6d4e38f80ccf2": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "ProgressStyleModel",
"state": {
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "ProgressStyleModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "StyleView",
"bar_color": null,
"description_width": ""
}
},
"517365223084483a8d8b59410c6fe95a": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "HTMLModel",
"state": {
"_dom_classes": [],
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "HTMLModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/controls",
"_view_module_version": "1.5.0",
"_view_name": "HTMLView",
"description": "",
"description_tooltip": null,
"layout": "IPY_MODEL_233836d2c7b048009a8d5f2039ff0483",
"placeholder": "",
"style": "IPY_MODEL_69fa12ed214d49df911ad7f7e4cf215b",
"value": "tokenizer_config.json: 100%"
}
},
"52081839832a457982c1415013515c97": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "HTMLModel",
"state": {
"_dom_classes": [],
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "HTMLModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/controls",
"_view_module_version": "1.5.0",
"_view_name": "HTMLView",
"description": "",
"description_tooltip": null,
"layout": "IPY_MODEL_8185830cefd94ee9805e4d79e8a20370",
"placeholder": "",
"style": "IPY_MODEL_268e472f9e5845fc895e167d0513aece",
"value": " 1/1 [00:03<00:00, 3.52s/it]"
}
},
"5259049306d74fa39e4184250a24c042": {
"model_module": "@jupyter-widgets/base",
"model_module_version": "1.2.0",
"model_name": "LayoutModel",
"state": {
"_model_module": "@jupyter-widgets/base",
"_model_module_version": "1.2.0",
"_model_name": "LayoutModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "LayoutView",
"align_content": null,
"align_items": null,
"align_self": null,
"border": null,
"bottom": null,
"display": null,
"flex": null,
"flex_flow": null,
"grid_area": null,
"grid_auto_columns": null,
"grid_auto_flow": null,
"grid_auto_rows": null,
"grid_column": null,
"grid_gap": null,
"grid_row": null,
"grid_template_areas": null,
"grid_template_columns": null,
"grid_template_rows": null,
"height": null,
"justify_content": null,
"justify_items": null,
"left": null,
"margin": null,
"max_height": null,
"max_width": null,
"min_height": null,
"min_width": null,
"object_fit": null,
"object_position": null,
"order": null,
"overflow": null,
"overflow_x": null,
"overflow_y": null,
"padding": null,
"right": null,
"top": null,
"visibility": null,
"width": null
}
},
"528b64da057d43c395ff2ce1147a8576": {
"model_module": "@jupyter-widgets/base",
"model_module_version": "1.2.0",
"model_name": "LayoutModel",
"state": {
"_model_module": "@jupyter-widgets/base",
"_model_module_version": "1.2.0",
"_model_name": "LayoutModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "LayoutView",
"align_content": null,
"align_items": null,
"align_self": null,
"border": null,
"bottom": null,
"display": null,
"flex": null,
"flex_flow": null,
"grid_area": null,
"grid_auto_columns": null,
"grid_auto_flow": null,
"grid_auto_rows": null,
"grid_column": null,
"grid_gap": null,
"grid_row": null,
"grid_template_areas": null,
"grid_template_columns": null,
"grid_template_rows": null,
"height": null,
"justify_content": null,
"justify_items": null,
"left": null,
"margin": null,
"max_height": null,
"max_width": null,
"min_height": null,
"min_width": null,
"object_fit": null,
"object_position": null,
"order": null,
"overflow": null,
"overflow_x": null,
"overflow_y": null,
"padding": null,
"right": null,
"top": null,
"visibility": null,
"width": null
}
},
"538539b1e9134709b26ac83664b5b114": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "DescriptionStyleModel",
"state": {
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "DescriptionStyleModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "StyleView",
"description_width": ""
}
},
"54205208826b40d28f6387784198101a": {
"model_module": "@jupyter-widgets/base",
"model_module_version": "1.2.0",
"model_name": "LayoutModel",
"state": {
"_model_module": "@jupyter-widgets/base",
"_model_module_version": "1.2.0",
"_model_name": "LayoutModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "LayoutView",
"align_content": null,
"align_items": null,
"align_self": null,
"border": null,
"bottom": null,
"display": null,
"flex": null,
"flex_flow": null,
"grid_area": null,
"grid_auto_columns": null,
"grid_auto_flow": null,
"grid_auto_rows": null,
"grid_column": null,
"grid_gap": null,
"grid_row": null,
"grid_template_areas": null,
"grid_template_columns": null,
"grid_template_rows": null,
"height": null,
"justify_content": null,
"justify_items": null,
"left": null,
"margin": null,
"max_height": null,
"max_width": null,
"min_height": null,
"min_width": null,
"object_fit": null,
"object_position": null,
"order": null,
"overflow": null,
"overflow_x": null,
"overflow_y": null,
"padding": null,
"right": null,
"top": null,
"visibility": null,
"width": null
}
},
"542a9b28ae904946a6fbbb57d1815e07": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "DescriptionStyleModel",
"state": {
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "DescriptionStyleModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "StyleView",
"description_width": ""
}
},
"58c7dee9928346aba7a1986e32a7a776": {
"model_module": "@jupyter-widgets/base",
"model_module_version": "1.2.0",
"model_name": "LayoutModel",
"state": {
"_model_module": "@jupyter-widgets/base",
"_model_module_version": "1.2.0",
"_model_name": "LayoutModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "LayoutView",
"align_content": null,
"align_items": null,
"align_self": null,
"border": null,
"bottom": null,
"display": null,
"flex": null,
"flex_flow": null,
"grid_area": null,
"grid_auto_columns": null,
"grid_auto_flow": null,
"grid_auto_rows": null,
"grid_column": null,
"grid_gap": null,
"grid_row": null,
"grid_template_areas": null,
"grid_template_columns": null,
"grid_template_rows": null,
"height": null,
"justify_content": null,
"justify_items": null,
"left": null,
"margin": null,
"max_height": null,
"max_width": null,
"min_height": null,
"min_width": null,
"object_fit": null,
"object_position": null,
"order": null,
"overflow": null,
"overflow_x": null,
"overflow_y": null,
"padding": null,
"right": null,
"top": null,
"visibility": null,
"width": null
}
},
"59cff3508e8b41a7a2923c19e0016ff4": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "DescriptionStyleModel",
"state": {
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "DescriptionStyleModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "StyleView",
"description_width": ""
}
},
"59fab15e1c644925b04e051a02b42fa6": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "HTMLModel",
"state": {
"_dom_classes": [],
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "HTMLModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/controls",
"_view_module_version": "1.5.0",
"_view_name": "HTMLView",
"description": "",
"description_tooltip": null,
"layout": "IPY_MODEL_7f35ec8e33ad453e905b9cad7a8cc2e5",
"placeholder": "",
"style": "IPY_MODEL_c9a42afb532542c78e86ff4618406c47",
"value": "100%"
}
},
"5ac8c654086747a6850b6462ccee2c35": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "DescriptionStyleModel",
"state": {
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "DescriptionStyleModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "StyleView",
"description_width": ""
}
},
"5b28753db78b45e3a083839ed0d71f17": {
"model_module": "@jupyter-widgets/base",
"model_module_version": "1.2.0",
"model_name": "LayoutModel",
"state": {
"_model_module": "@jupyter-widgets/base",
"_model_module_version": "1.2.0",
"_model_name": "LayoutModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "LayoutView",
"align_content": null,
"align_items": null,
"align_self": null,
"border": null,
"bottom": null,
"display": null,
"flex": null,
"flex_flow": null,
"grid_area": null,
"grid_auto_columns": null,
"grid_auto_flow": null,
"grid_auto_rows": null,
"grid_column": null,
"grid_gap": null,
"grid_row": null,
"grid_template_areas": null,
"grid_template_columns": null,
"grid_template_rows": null,
"height": null,
"justify_content": null,
"justify_items": null,
"left": null,
"margin": null,
"max_height": null,
"max_width": null,
"min_height": null,
"min_width": null,
"object_fit": null,
"object_position": null,
"order": null,
"overflow": null,
"overflow_x": null,
"overflow_y": null,
"padding": null,
"right": null,
"top": null,
"visibility": null,
"width": null
}
},
"5c15f734bd2c4caeb1d0682cdfb6053a": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "HBoxModel",
"state": {
"_dom_classes": [],
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "HBoxModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/controls",
"_view_module_version": "1.5.0",
"_view_name": "HBoxView",
"box_style": "",
"children": [
"IPY_MODEL_e202f31c8f854fa19844b176bc2917c2",
"IPY_MODEL_17e3bbf2df974aa1b840e4511ed76afd",
"IPY_MODEL_758310411c2c4c7bb318d082ed1cecf1"
],
"layout": "IPY_MODEL_f73f729c27414608b106a61357ef1f9b"
}
},
"5d69c9c0eb454c998628d042720175c2": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "DescriptionStyleModel",
"state": {
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "DescriptionStyleModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "StyleView",
"description_width": ""
}
},
"62e5a5dea5fe404fb6b54561b17dfed2": {
"model_module": "@jupyter-widgets/base",
"model_module_version": "1.2.0",
"model_name": "LayoutModel",
"state": {
"_model_module": "@jupyter-widgets/base",
"_model_module_version": "1.2.0",
"_model_name": "LayoutModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "LayoutView",
"align_content": null,
"align_items": null,
"align_self": null,
"border": null,
"bottom": null,
"display": null,
"flex": null,
"flex_flow": null,
"grid_area": null,
"grid_auto_columns": null,
"grid_auto_flow": null,
"grid_auto_rows": null,
"grid_column": null,
"grid_gap": null,
"grid_row": null,
"grid_template_areas": null,
"grid_template_columns": null,
"grid_template_rows": null,
"height": null,
"justify_content": null,
"justify_items": null,
"left": null,
"margin": null,
"max_height": null,
"max_width": null,
"min_height": null,
"min_width": null,
"object_fit": null,
"object_position": null,
"order": null,
"overflow": null,
"overflow_x": null,
"overflow_y": null,
"padding": null,
"right": null,
"top": null,
"visibility": null,
"width": null
}
},
"635701e66e4f44b39ee094f1e3953af9": {
"model_module": "@jupyter-widgets/base",
"model_module_version": "1.2.0",
"model_name": "LayoutModel",
"state": {
"_model_module": "@jupyter-widgets/base",
"_model_module_version": "1.2.0",
"_model_name": "LayoutModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "LayoutView",
"align_content": null,
"align_items": null,
"align_self": null,
"border": null,
"bottom": null,
"display": null,
"flex": null,
"flex_flow": null,
"grid_area": null,
"grid_auto_columns": null,
"grid_auto_flow": null,
"grid_auto_rows": null,
"grid_column": null,
"grid_gap": null,
"grid_row": null,
"grid_template_areas": null,
"grid_template_columns": null,
"grid_template_rows": null,
"height": null,
"justify_content": null,
"justify_items": null,
"left": null,
"margin": null,
"max_height": null,
"max_width": null,
"min_height": null,
"min_width": null,
"object_fit": null,
"object_position": null,
"order": null,
"overflow": null,
"overflow_x": null,
"overflow_y": null,
"padding": null,
"right": null,
"top": null,
"visibility": null,
"width": null
}
},
"66996de2024046ff9801f1d36859098c": {
"model_module": "@jupyter-widgets/base",
"model_module_version": "1.2.0",
"model_name": "LayoutModel",
"state": {
"_model_module": "@jupyter-widgets/base",
"_model_module_version": "1.2.0",
"_model_name": "LayoutModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "LayoutView",
"align_content": null,
"align_items": null,
"align_self": null,
"border": null,
"bottom": null,
"display": null,
"flex": null,
"flex_flow": null,
"grid_area": null,
"grid_auto_columns": null,
"grid_auto_flow": null,
"grid_auto_rows": null,
"grid_column": null,
"grid_gap": null,
"grid_row": null,
"grid_template_areas": null,
"grid_template_columns": null,
"grid_template_rows": null,
"height": null,
"justify_content": null,
"justify_items": null,
"left": null,
"margin": null,
"max_height": null,
"max_width": null,
"min_height": null,
"min_width": null,
"object_fit": null,
"object_position": null,
"order": null,
"overflow": null,
"overflow_x": null,
"overflow_y": null,
"padding": null,
"right": null,
"top": null,
"visibility": null,
"width": null
}
},
"67793453c68943329ccd77c0b5200f2a": {
"model_module": "@jupyter-widgets/base",
"model_module_version": "1.2.0",
"model_name": "LayoutModel",
"state": {
"_model_module": "@jupyter-widgets/base",
"_model_module_version": "1.2.0",
"_model_name": "LayoutModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "LayoutView",
"align_content": null,
"align_items": null,
"align_self": null,
"border": null,
"bottom": null,
"display": null,
"flex": null,
"flex_flow": null,
"grid_area": null,
"grid_auto_columns": null,
"grid_auto_flow": null,
"grid_auto_rows": null,
"grid_column": null,
"grid_gap": null,
"grid_row": null,
"grid_template_areas": null,
"grid_template_columns": null,
"grid_template_rows": null,
"height": null,
"justify_content": null,
"justify_items": null,
"left": null,
"margin": null,
"max_height": null,
"max_width": null,
"min_height": null,
"min_width": null,
"object_fit": null,
"object_position": null,
"order": null,
"overflow": null,
"overflow_x": null,
"overflow_y": null,
"padding": null,
"right": null,
"top": null,
"visibility": null,
"width": null
}
},
"677de59ed6a941eb980abac52eae5a69": {
"model_module": "@jupyter-widgets/base",
"model_module_version": "1.2.0",
"model_name": "LayoutModel",
"state": {
"_model_module": "@jupyter-widgets/base",
"_model_module_version": "1.2.0",
"_model_name": "LayoutModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "LayoutView",
"align_content": null,
"align_items": null,
"align_self": null,
"border": null,
"bottom": null,
"display": null,
"flex": null,
"flex_flow": null,
"grid_area": null,
"grid_auto_columns": null,
"grid_auto_flow": null,
"grid_auto_rows": null,
"grid_column": null,
"grid_gap": null,
"grid_row": null,
"grid_template_areas": null,
"grid_template_columns": null,
"grid_template_rows": null,
"height": null,
"justify_content": null,
"justify_items": null,
"left": null,
"margin": null,
"max_height": null,
"max_width": null,
"min_height": null,
"min_width": null,
"object_fit": null,
"object_position": null,
"order": null,
"overflow": null,
"overflow_x": null,
"overflow_y": null,
"padding": null,
"right": null,
"top": null,
"visibility": null,
"width": null
}
},
"6869bd240f6a4c27b19fa101cc665001": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "FloatProgressModel",
"state": {
"_dom_classes": [],
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "FloatProgressModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/controls",
"_view_module_version": "1.5.0",
"_view_name": "ProgressView",
"bar_style": "danger",
"description": "",
"description_tooltip": null,
"layout": "IPY_MODEL_58c7dee9928346aba7a1986e32a7a776",
"max": 143810826,
"min": 0,
"orientation": "horizontal",
"style": "IPY_MODEL_2595d0c6016849d999725fe309b38414",
"value": 143810813
}
},
"6889ef6686684e8faee29a64986488ad": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "HTMLModel",
"state": {
"_dom_classes": [],
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "HTMLModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/controls",
"_view_module_version": "1.5.0",
"_view_name": "HTMLView",
"description": "",
"description_tooltip": null,
"layout": "IPY_MODEL_3b208739190647aba89d38664f3c04ff",
"placeholder": "",
"style": "IPY_MODEL_13858c39f00043eab784b43e78f75e96",
"value": "model.safetensors: 100%"
}
},
"6894219580074769999b672cb6e677cd": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "DescriptionStyleModel",
"state": {
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "DescriptionStyleModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "StyleView",
"description_width": ""
}
},
"69fa12ed214d49df911ad7f7e4cf215b": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "DescriptionStyleModel",
"state": {
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "DescriptionStyleModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "StyleView",
"description_width": ""
}
},
"6a0264ad9e1045e9b276da5afea538e4": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "HBoxModel",
"state": {
"_dom_classes": [],
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "HBoxModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/controls",
"_view_module_version": "1.5.0",
"_view_name": "HBoxView",
"box_style": "",
"children": [
"IPY_MODEL_6889ef6686684e8faee29a64986488ad",
"IPY_MODEL_28575a44bd4a4ff4995bef61a1ff923f",
"IPY_MODEL_ac2708c092394bdfbad40e65c5fcf5bd"
],
"layout": "IPY_MODEL_362a469d210a40c4beb44614d0dff94d"
}
},
"6dba4a23cf4547adb17eaf446eef7297": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "HTMLModel",
"state": {
"_dom_classes": [],
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "HTMLModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/controls",
"_view_module_version": "1.5.0",
"_view_name": "HTMLView",
"description": "",
"description_tooltip": null,
"layout": "IPY_MODEL_9c6d70b74f3d4c0c9fce7e8c379a4d2f",
"placeholder": "",
"style": "IPY_MODEL_538539b1e9134709b26ac83664b5b114",
"value": " 137k/137k [00:00<00:00, 629kB/s]"
}
},
"6ded895c12da47c89d0238e8ee66d11a": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "HBoxModel",
"state": {
"_dom_classes": [],
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "HBoxModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/controls",
"_view_module_version": "1.5.0",
"_view_name": "HBoxView",
"box_style": "",
"children": [
"IPY_MODEL_4962b782c5ca4670af98825a3438ac13",
"IPY_MODEL_cde99f9f0c26432fbf9c34ee12f04852",
"IPY_MODEL_2db4c72d8b2448ffad721123c1641cc7"
],
"layout": "IPY_MODEL_9a33b54ab97449aa90aa43c3a017a419"
}
},
"6e394dc9bb584d7b84885265267f2174": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "DescriptionStyleModel",
"state": {
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "DescriptionStyleModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "StyleView",
"description_width": ""
}
},
"6f3bafec64374b68af5d6bc79774951d": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "DescriptionStyleModel",
"state": {
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "DescriptionStyleModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "StyleView",
"description_width": ""
}
},
"7040bb77fe904a378382fb8f0bb3ac3f": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "HTMLModel",
"state": {
"_dom_classes": [],
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "HTMLModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/controls",
"_view_module_version": "1.5.0",
"_view_name": "HTMLView",
"description": "",
"description_tooltip": null,
"layout": "IPY_MODEL_aba4df1d6c5b4fde90452a6d6241cb9f",
"placeholder": "",
"style": "IPY_MODEL_59cff3508e8b41a7a2923c19e0016ff4",
"value": " 172026/172026 [00:12<00:00, 14513.54 examples/s]"
}
},
"71d2164bd80c4c7ebdba192b545307e0": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "ProgressStyleModel",
"state": {
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "ProgressStyleModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "StyleView",
"bar_color": null,
"description_width": ""
}
},
"722ae7185340428ea42f1f0322d11811": {
"model_module": "@jupyter-widgets/base",
"model_module_version": "1.2.0",
"model_name": "LayoutModel",
"state": {
"_model_module": "@jupyter-widgets/base",
"_model_module_version": "1.2.0",
"_model_name": "LayoutModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "LayoutView",
"align_content": null,
"align_items": null,
"align_self": null,
"border": null,
"bottom": null,
"display": null,
"flex": null,
"flex_flow": null,
"grid_area": null,
"grid_auto_columns": null,
"grid_auto_flow": null,
"grid_auto_rows": null,
"grid_column": null,
"grid_gap": null,
"grid_row": null,
"grid_template_areas": null,
"grid_template_columns": null,
"grid_template_rows": null,
"height": null,
"justify_content": null,
"justify_items": null,
"left": null,
"margin": null,
"max_height": null,
"max_width": null,
"min_height": null,
"min_width": null,
"object_fit": null,
"object_position": null,
"order": null,
"overflow": null,
"overflow_x": null,
"overflow_y": null,
"padding": null,
"right": null,
"top": null,
"visibility": null,
"width": null
}
},
"730d88a3a02e4b528efd0b7a5b4bbe51": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "DescriptionStyleModel",
"state": {
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "DescriptionStyleModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "StyleView",
"description_width": ""
}
},
"749165aa361b47eda47e778a37176012": {
"model_module": "@jupyter-widgets/base",
"model_module_version": "1.2.0",
"model_name": "LayoutModel",
"state": {
"_model_module": "@jupyter-widgets/base",
"_model_module_version": "1.2.0",
"_model_name": "LayoutModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "LayoutView",
"align_content": null,
"align_items": null,
"align_self": null,
"border": null,
"bottom": null,
"display": null,
"flex": null,
"flex_flow": null,
"grid_area": null,
"grid_auto_columns": null,
"grid_auto_flow": null,
"grid_auto_rows": null,
"grid_column": null,
"grid_gap": null,
"grid_row": null,
"grid_template_areas": null,
"grid_template_columns": null,
"grid_template_rows": null,
"height": null,
"justify_content": null,
"justify_items": null,
"left": null,
"margin": null,
"max_height": null,
"max_width": null,
"min_height": null,
"min_width": null,
"object_fit": null,
"object_position": null,
"order": null,
"overflow": null,
"overflow_x": null,
"overflow_y": null,
"padding": null,
"right": null,
"top": null,
"visibility": null,
"width": null
}
},
"758310411c2c4c7bb318d082ed1cecf1": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "HTMLModel",
"state": {
"_dom_classes": [],
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "HTMLModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/controls",
"_view_module_version": "1.5.0",
"_view_name": "HTMLView",
"description": "",
"description_tooltip": null,
"layout": "IPY_MODEL_abf15b1dd4f548229fdec015657aed73",
"placeholder": "",
"style": "IPY_MODEL_1a4e9b55836f42cfbb36fc4f0a01252c",
"value": " 172026/172026 [03:09<00:00, 794.35 examples/s]"
}
},
"7677cdddfa104dc9bdc352596fd57679": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "HTMLModel",
"state": {
"_dom_classes": [],
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "HTMLModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/controls",
"_view_module_version": "1.5.0",
"_view_name": "HTMLView",
"description": "",
"description_tooltip": null,
"layout": "IPY_MODEL_5259049306d74fa39e4184250a24c042",
"placeholder": "",
"style": "IPY_MODEL_8c9fd310580848ca8cc29b9b1bedc034",
"value": "adapter_model.safetensors: "
}
},
"7943696966dd4434900e30aed33fafda": {
"model_module": "@jupyter-widgets/base",
"model_module_version": "1.2.0",
"model_name": "LayoutModel",
"state": {
"_model_module": "@jupyter-widgets/base",
"_model_module_version": "1.2.0",
"_model_name": "LayoutModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "LayoutView",
"align_content": null,
"align_items": null,
"align_self": null,
"border": null,
"bottom": null,
"display": null,
"flex": null,
"flex_flow": null,
"grid_area": null,
"grid_auto_columns": null,
"grid_auto_flow": null,
"grid_auto_rows": null,
"grid_column": null,
"grid_gap": null,
"grid_row": null,
"grid_template_areas": null,
"grid_template_columns": null,
"grid_template_rows": null,
"height": null,
"justify_content": null,
"justify_items": null,
"left": null,
"margin": null,
"max_height": null,
"max_width": null,
"min_height": null,
"min_width": null,
"object_fit": null,
"object_position": null,
"order": null,
"overflow": null,
"overflow_x": null,
"overflow_y": null,
"padding": null,
"right": null,
"top": null,
"visibility": null,
"width": null
}
},
"79d52fabb462442a97f443c6b361f213": {
"model_module": "@jupyter-widgets/base",
"model_module_version": "1.2.0",
"model_name": "LayoutModel",
"state": {
"_model_module": "@jupyter-widgets/base",
"_model_module_version": "1.2.0",
"_model_name": "LayoutModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "LayoutView",
"align_content": null,
"align_items": null,
"align_self": null,
"border": null,
"bottom": null,
"display": null,
"flex": null,
"flex_flow": null,
"grid_area": null,
"grid_auto_columns": null,
"grid_auto_flow": null,
"grid_auto_rows": null,
"grid_column": null,
"grid_gap": null,
"grid_row": null,
"grid_template_areas": null,
"grid_template_columns": null,
"grid_template_rows": null,
"height": null,
"justify_content": null,
"justify_items": null,
"left": null,
"margin": null,
"max_height": null,
"max_width": null,
"min_height": null,
"min_width": null,
"object_fit": null,
"object_position": null,
"order": null,
"overflow": null,
"overflow_x": null,
"overflow_y": null,
"padding": null,
"right": null,
"top": null,
"visibility": null,
"width": null
}
},
"7bb43fd56e754302bbe77c083996fa97": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "DescriptionStyleModel",
"state": {
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "DescriptionStyleModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "StyleView",
"description_width": ""
}
},
"7d7f3cdde6e7482580883140dd1ba3ee": {
"model_module": "@jupyter-widgets/base",
"model_module_version": "1.2.0",
"model_name": "LayoutModel",
"state": {
"_model_module": "@jupyter-widgets/base",
"_model_module_version": "1.2.0",
"_model_name": "LayoutModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "LayoutView",
"align_content": null,
"align_items": null,
"align_self": null,
"border": null,
"bottom": null,
"display": null,
"flex": null,
"flex_flow": null,
"grid_area": null,
"grid_auto_columns": null,
"grid_auto_flow": null,
"grid_auto_rows": null,
"grid_column": null,
"grid_gap": null,
"grid_row": null,
"grid_template_areas": null,
"grid_template_columns": null,
"grid_template_rows": null,
"height": null,
"justify_content": null,
"justify_items": null,
"left": null,
"margin": null,
"max_height": null,
"max_width": null,
"min_height": null,
"min_width": null,
"object_fit": null,
"object_position": null,
"order": null,
"overflow": null,
"overflow_x": null,
"overflow_y": null,
"padding": null,
"right": null,
"top": null,
"visibility": null,
"width": null
}
},
"7e0bca45410b467c92f97deaaf153ce6": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "HTMLModel",
"state": {
"_dom_classes": [],
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "HTMLModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/controls",
"_view_module_version": "1.5.0",
"_view_name": "HTMLView",
"description": "",
"description_tooltip": null,
"layout": "IPY_MODEL_4664916ffbe54f33adbf1b416fd5f384",
"placeholder": "",
"style": "IPY_MODEL_6f3bafec64374b68af5d6bc79774951d",
"value": "special_tokens_map.json: 100%"
}
},
"7f35ec8e33ad453e905b9cad7a8cc2e5": {
"model_module": "@jupyter-widgets/base",
"model_module_version": "1.2.0",
"model_name": "LayoutModel",
"state": {
"_model_module": "@jupyter-widgets/base",
"_model_module_version": "1.2.0",
"_model_name": "LayoutModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "LayoutView",
"align_content": null,
"align_items": null,
"align_self": null,
"border": null,
"bottom": null,
"display": null,
"flex": null,
"flex_flow": null,
"grid_area": null,
"grid_auto_columns": null,
"grid_auto_flow": null,
"grid_auto_rows": null,
"grid_column": null,
"grid_gap": null,
"grid_row": null,
"grid_template_areas": null,
"grid_template_columns": null,
"grid_template_rows": null,
"height": null,
"justify_content": null,
"justify_items": null,
"left": null,
"margin": null,
"max_height": null,
"max_width": null,
"min_height": null,
"min_width": null,
"object_fit": null,
"object_position": null,
"order": null,
"overflow": null,
"overflow_x": null,
"overflow_y": null,
"padding": null,
"right": null,
"top": null,
"visibility": null,
"width": null
}
},
"8057d60eab0843d1bcb06ff794b911aa": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "ProgressStyleModel",
"state": {
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "ProgressStyleModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "StyleView",
"bar_color": null,
"description_width": ""
}
},
"812857d3b17b403f989b3686cd520c02": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "HTMLModel",
"state": {
"_dom_classes": [],
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "HTMLModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/controls",
"_view_module_version": "1.5.0",
"_view_name": "HTMLView",
"description": "",
"description_tooltip": null,
"layout": "IPY_MODEL_1b5347ed1b584555b82fe2e064595c67",
"placeholder": "",
"style": "IPY_MODEL_4db8741fb5334720b19a134b0686eaea",
"value": "100%"
}
},
"8185830cefd94ee9805e4d79e8a20370": {
"model_module": "@jupyter-widgets/base",
"model_module_version": "1.2.0",
"model_name": "LayoutModel",
"state": {
"_model_module": "@jupyter-widgets/base",
"_model_module_version": "1.2.0",
"_model_name": "LayoutModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "LayoutView",
"align_content": null,
"align_items": null,
"align_self": null,
"border": null,
"bottom": null,
"display": null,
"flex": null,
"flex_flow": null,
"grid_area": null,
"grid_auto_columns": null,
"grid_auto_flow": null,
"grid_auto_rows": null,
"grid_column": null,
"grid_gap": null,
"grid_row": null,
"grid_template_areas": null,
"grid_template_columns": null,
"grid_template_rows": null,
"height": null,
"justify_content": null,
"justify_items": null,
"left": null,
"margin": null,
"max_height": null,
"max_width": null,
"min_height": null,
"min_width": null,
"object_fit": null,
"object_position": null,
"order": null,
"overflow": null,
"overflow_x": null,
"overflow_y": null,
"padding": null,
"right": null,
"top": null,
"visibility": null,
"width": null
}
},
"82c8aca0f1a24c38a2c111dfa85df233": {
"model_module": "@jupyter-widgets/base",
"model_module_version": "1.2.0",
"model_name": "LayoutModel",
"state": {
"_model_module": "@jupyter-widgets/base",
"_model_module_version": "1.2.0",
"_model_name": "LayoutModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "LayoutView",
"align_content": null,
"align_items": null,
"align_self": null,
"border": null,
"bottom": null,
"display": null,
"flex": null,
"flex_flow": null,
"grid_area": null,
"grid_auto_columns": null,
"grid_auto_flow": null,
"grid_auto_rows": null,
"grid_column": null,
"grid_gap": null,
"grid_row": null,
"grid_template_areas": null,
"grid_template_columns": null,
"grid_template_rows": null,
"height": null,
"justify_content": null,
"justify_items": null,
"left": null,
"margin": null,
"max_height": null,
"max_width": null,
"min_height": null,
"min_width": null,
"object_fit": null,
"object_position": null,
"order": null,
"overflow": null,
"overflow_x": null,
"overflow_y": null,
"padding": null,
"right": null,
"top": null,
"visibility": null,
"width": null
}
},
"843bc72177104b4782b95cb2f741129a": {
"model_module": "@jupyter-widgets/base",
"model_module_version": "1.2.0",
"model_name": "LayoutModel",
"state": {
"_model_module": "@jupyter-widgets/base",
"_model_module_version": "1.2.0",
"_model_name": "LayoutModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "LayoutView",
"align_content": null,
"align_items": null,
"align_self": null,
"border": null,
"bottom": null,
"display": null,
"flex": null,
"flex_flow": null,
"grid_area": null,
"grid_auto_columns": null,
"grid_auto_flow": null,
"grid_auto_rows": null,
"grid_column": null,
"grid_gap": null,
"grid_row": null,
"grid_template_areas": null,
"grid_template_columns": null,
"grid_template_rows": null,
"height": null,
"justify_content": null,
"justify_items": null,
"left": null,
"margin": null,
"max_height": null,
"max_width": null,
"min_height": null,
"min_width": null,
"object_fit": null,
"object_position": null,
"order": null,
"overflow": null,
"overflow_x": null,
"overflow_y": null,
"padding": null,
"right": null,
"top": null,
"visibility": null,
"width": null
}
},
"856c8aab5f8e451ebc7e19e79105ed0b": {
"model_module": "@jupyter-widgets/base",
"model_module_version": "1.2.0",
"model_name": "LayoutModel",
"state": {
"_model_module": "@jupyter-widgets/base",
"_model_module_version": "1.2.0",
"_model_name": "LayoutModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "LayoutView",
"align_content": null,
"align_items": null,
"align_self": null,
"border": null,
"bottom": null,
"display": null,
"flex": null,
"flex_flow": null,
"grid_area": null,
"grid_auto_columns": null,
"grid_auto_flow": null,
"grid_auto_rows": null,
"grid_column": null,
"grid_gap": null,
"grid_row": null,
"grid_template_areas": null,
"grid_template_columns": null,
"grid_template_rows": null,
"height": null,
"justify_content": null,
"justify_items": null,
"left": null,
"margin": null,
"max_height": null,
"max_width": null,
"min_height": null,
"min_width": null,
"object_fit": null,
"object_position": null,
"order": null,
"overflow": null,
"overflow_x": null,
"overflow_y": null,
"padding": null,
"right": null,
"top": null,
"visibility": null,
"width": null
}
},
"8657ee65ecd84d5a9060532e3120ebc2": {
"model_module": "@jupyter-widgets/base",
"model_module_version": "1.2.0",
"model_name": "LayoutModel",
"state": {
"_model_module": "@jupyter-widgets/base",
"_model_module_version": "1.2.0",
"_model_name": "LayoutModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "LayoutView",
"align_content": null,
"align_items": null,
"align_self": null,
"border": null,
"bottom": null,
"display": null,
"flex": null,
"flex_flow": null,
"grid_area": null,
"grid_auto_columns": null,
"grid_auto_flow": null,
"grid_auto_rows": null,
"grid_column": null,
"grid_gap": null,
"grid_row": null,
"grid_template_areas": null,
"grid_template_columns": null,
"grid_template_rows": null,
"height": null,
"justify_content": null,
"justify_items": null,
"left": null,
"margin": null,
"max_height": null,
"max_width": null,
"min_height": null,
"min_width": null,
"object_fit": null,
"object_position": null,
"order": null,
"overflow": null,
"overflow_x": null,
"overflow_y": null,
"padding": null,
"right": null,
"top": null,
"visibility": null,
"width": null
}
},
"86dc1f03a7384d7b926c83ba9ad67625": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "FloatProgressModel",
"state": {
"_dom_classes": [],
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "FloatProgressModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/controls",
"_view_module_version": "1.5.0",
"_view_name": "ProgressView",
"bar_style": "success",
"description": "",
"description_tooltip": null,
"layout": "IPY_MODEL_25fc5fc784a44aa491b841f185ef374d",
"max": 450,
"min": 0,
"orientation": "horizontal",
"style": "IPY_MODEL_b882d5d3ca8442aaa2ddef15e47e5b45",
"value": 450
}
},
"8c9fd310580848ca8cc29b9b1bedc034": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "DescriptionStyleModel",
"state": {
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "DescriptionStyleModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "StyleView",
"description_width": ""
}
},
"8e2ad3625e624f7ba3ade89be147652d": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "DescriptionStyleModel",
"state": {
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "DescriptionStyleModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "StyleView",
"description_width": ""
}
},
"93538debadaf4cad9b3563ea1b7c7e74": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "DescriptionStyleModel",
"state": {
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "DescriptionStyleModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "StyleView",
"description_width": ""
}
},
"974e02c218174ee3ac8f7097205dbea3": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "HBoxModel",
"state": {
"_dom_classes": [],
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "HBoxModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/controls",
"_view_module_version": "1.5.0",
"_view_name": "HBoxView",
"box_style": "",
"children": [
"IPY_MODEL_b4c1a2579601463eae261e9d8d519658",
"IPY_MODEL_168b4bc0ddd548cc8e3632eee17f6333",
"IPY_MODEL_b79b90dfab6340b19cd27f40c497420d"
],
"layout": "IPY_MODEL_429d057b1f4b46b1a59deff19df8c51f"
}
},
"9827853eb4ff417387631c3bc95e5d49": {
"model_module": "@jupyter-widgets/base",
"model_module_version": "1.2.0",
"model_name": "LayoutModel",
"state": {
"_model_module": "@jupyter-widgets/base",
"_model_module_version": "1.2.0",
"_model_name": "LayoutModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "LayoutView",
"align_content": null,
"align_items": null,
"align_self": null,
"border": null,
"bottom": null,
"display": null,
"flex": null,
"flex_flow": null,
"grid_area": null,
"grid_auto_columns": null,
"grid_auto_flow": null,
"grid_auto_rows": null,
"grid_column": null,
"grid_gap": null,
"grid_row": null,
"grid_template_areas": null,
"grid_template_columns": null,
"grid_template_rows": null,
"height": null,
"justify_content": null,
"justify_items": null,
"left": null,
"margin": null,
"max_height": null,
"max_width": null,
"min_height": null,
"min_width": null,
"object_fit": null,
"object_position": null,
"order": null,
"overflow": null,
"overflow_x": null,
"overflow_y": null,
"padding": null,
"right": null,
"top": null,
"visibility": null,
"width": null
}
},
"9a33b54ab97449aa90aa43c3a017a419": {
"model_module": "@jupyter-widgets/base",
"model_module_version": "1.2.0",
"model_name": "LayoutModel",
"state": {
"_model_module": "@jupyter-widgets/base",
"_model_module_version": "1.2.0",
"_model_name": "LayoutModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "LayoutView",
"align_content": null,
"align_items": null,
"align_self": null,
"border": null,
"bottom": null,
"display": null,
"flex": null,
"flex_flow": null,
"grid_area": null,
"grid_auto_columns": null,
"grid_auto_flow": null,
"grid_auto_rows": null,
"grid_column": null,
"grid_gap": null,
"grid_row": null,
"grid_template_areas": null,
"grid_template_columns": null,
"grid_template_rows": null,
"height": null,
"justify_content": null,
"justify_items": null,
"left": null,
"margin": null,
"max_height": null,
"max_width": null,
"min_height": null,
"min_width": null,
"object_fit": null,
"object_position": null,
"order": null,
"overflow": null,
"overflow_x": null,
"overflow_y": null,
"padding": null,
"right": null,
"top": null,
"visibility": null,
"width": null
}
},
"9ad7254e49c84949a63df3569a9f6a34": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "FloatProgressModel",
"state": {
"_dom_classes": [],
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "FloatProgressModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/controls",
"_view_module_version": "1.5.0",
"_view_name": "ProgressView",
"bar_style": "danger",
"description": "",
"description_tooltip": null,
"layout": "IPY_MODEL_9fe9c71e86824b8ba7f6757fb961f769",
"max": 158165675,
"min": 0,
"orientation": "horizontal",
"style": "IPY_MODEL_37aeacc4ed6349b096efc3513d027c53",
"value": 158165660
}
},
"9b1d1d58b37f4c0d8d43cd0bfe013238": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "HBoxModel",
"state": {
"_dom_classes": [],
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "HBoxModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/controls",
"_view_module_version": "1.5.0",
"_view_name": "HBoxView",
"box_style": "",
"children": [
"IPY_MODEL_59fab15e1c644925b04e051a02b42fa6",
"IPY_MODEL_48aeec0877b54f7bab9cdb19e5792d6b",
"IPY_MODEL_f751fcf5656b4240a576a0f4f309c51f"
],
"layout": "IPY_MODEL_a73546aa20c54fc6aa8e414ebd91a336"
}
},
"9c3c23ca3aab4f72ba94c8dc769d8e92": {
"model_module": "@jupyter-widgets/base",
"model_module_version": "1.2.0",
"model_name": "LayoutModel",
"state": {
"_model_module": "@jupyter-widgets/base",
"_model_module_version": "1.2.0",
"_model_name": "LayoutModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "LayoutView",
"align_content": null,
"align_items": null,
"align_self": null,
"border": null,
"bottom": null,
"display": null,
"flex": null,
"flex_flow": null,
"grid_area": null,
"grid_auto_columns": null,
"grid_auto_flow": null,
"grid_auto_rows": null,
"grid_column": null,
"grid_gap": null,
"grid_row": null,
"grid_template_areas": null,
"grid_template_columns": null,
"grid_template_rows": null,
"height": null,
"justify_content": null,
"justify_items": null,
"left": null,
"margin": null,
"max_height": null,
"max_width": null,
"min_height": null,
"min_width": null,
"object_fit": null,
"object_position": null,
"order": null,
"overflow": null,
"overflow_x": null,
"overflow_y": null,
"padding": null,
"right": null,
"top": null,
"visibility": null,
"width": null
}
},
"9c4f0814b946400c8d35d973a8907f8a": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "DescriptionStyleModel",
"state": {
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "DescriptionStyleModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "StyleView",
"description_width": ""
}
},
"9c6d70b74f3d4c0c9fce7e8c379a4d2f": {
"model_module": "@jupyter-widgets/base",
"model_module_version": "1.2.0",
"model_name": "LayoutModel",
"state": {
"_model_module": "@jupyter-widgets/base",
"_model_module_version": "1.2.0",
"_model_name": "LayoutModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "LayoutView",
"align_content": null,
"align_items": null,
"align_self": null,
"border": null,
"bottom": null,
"display": null,
"flex": null,
"flex_flow": null,
"grid_area": null,
"grid_auto_columns": null,
"grid_auto_flow": null,
"grid_auto_rows": null,
"grid_column": null,
"grid_gap": null,
"grid_row": null,
"grid_template_areas": null,
"grid_template_columns": null,
"grid_template_rows": null,
"height": null,
"justify_content": null,
"justify_items": null,
"left": null,
"margin": null,
"max_height": null,
"max_width": null,
"min_height": null,
"min_width": null,
"object_fit": null,
"object_position": null,
"order": null,
"overflow": null,
"overflow_x": null,
"overflow_y": null,
"padding": null,
"right": null,
"top": null,
"visibility": null,
"width": null
}
},
"9ce97683d0d14b8682b88d297b05e1e8": {
"model_module": "@jupyter-widgets/base",
"model_module_version": "1.2.0",
"model_name": "LayoutModel",
"state": {
"_model_module": "@jupyter-widgets/base",
"_model_module_version": "1.2.0",
"_model_name": "LayoutModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "LayoutView",
"align_content": null,
"align_items": null,
"align_self": null,
"border": null,
"bottom": null,
"display": null,
"flex": null,
"flex_flow": null,
"grid_area": null,
"grid_auto_columns": null,
"grid_auto_flow": null,
"grid_auto_rows": null,
"grid_column": null,
"grid_gap": null,
"grid_row": null,
"grid_template_areas": null,
"grid_template_columns": null,
"grid_template_rows": null,
"height": null,
"justify_content": null,
"justify_items": null,
"left": null,
"margin": null,
"max_height": null,
"max_width": null,
"min_height": null,
"min_width": null,
"object_fit": null,
"object_position": null,
"order": null,
"overflow": null,
"overflow_x": null,
"overflow_y": null,
"padding": null,
"right": null,
"top": null,
"visibility": null,
"width": null
}
},
"9dc305d92ded49e58e76469d67d9a2a7": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "DescriptionStyleModel",
"state": {
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "DescriptionStyleModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "StyleView",
"description_width": ""
}
},
"9e51e029a44145c4ab2572cf91841696": {
"model_module": "@jupyter-widgets/base",
"model_module_version": "1.2.0",
"model_name": "LayoutModel",
"state": {
"_model_module": "@jupyter-widgets/base",
"_model_module_version": "1.2.0",
"_model_name": "LayoutModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "LayoutView",
"align_content": null,
"align_items": null,
"align_self": null,
"border": null,
"bottom": null,
"display": null,
"flex": null,
"flex_flow": null,
"grid_area": null,
"grid_auto_columns": null,
"grid_auto_flow": null,
"grid_auto_rows": null,
"grid_column": null,
"grid_gap": null,
"grid_row": null,
"grid_template_areas": null,
"grid_template_columns": null,
"grid_template_rows": null,
"height": null,
"justify_content": null,
"justify_items": null,
"left": null,
"margin": null,
"max_height": null,
"max_width": null,
"min_height": null,
"min_width": null,
"object_fit": null,
"object_position": null,
"order": null,
"overflow": null,
"overflow_x": null,
"overflow_y": null,
"padding": null,
"right": null,
"top": null,
"visibility": null,
"width": null
}
},
"9eeec3eb1b384a51b606d71e8ad9a171": {
"model_module": "@jupyter-widgets/base",
"model_module_version": "1.2.0",
"model_name": "LayoutModel",
"state": {
"_model_module": "@jupyter-widgets/base",
"_model_module_version": "1.2.0",
"_model_name": "LayoutModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "LayoutView",
"align_content": null,
"align_items": null,
"align_self": null,
"border": null,
"bottom": null,
"display": null,
"flex": null,
"flex_flow": null,
"grid_area": null,
"grid_auto_columns": null,
"grid_auto_flow": null,
"grid_auto_rows": null,
"grid_column": null,
"grid_gap": null,
"grid_row": null,
"grid_template_areas": null,
"grid_template_columns": null,
"grid_template_rows": null,
"height": null,
"justify_content": null,
"justify_items": null,
"left": null,
"margin": null,
"max_height": null,
"max_width": null,
"min_height": null,
"min_width": null,
"object_fit": null,
"object_position": null,
"order": null,
"overflow": null,
"overflow_x": null,
"overflow_y": null,
"padding": null,
"right": null,
"top": null,
"visibility": null,
"width": null
}
},
"9f7cf13438a84bb29002d4dcf9583fd4": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "ProgressStyleModel",
"state": {
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "ProgressStyleModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "StyleView",
"bar_color": null,
"description_width": ""
}
},
"9fe9c71e86824b8ba7f6757fb961f769": {
"model_module": "@jupyter-widgets/base",
"model_module_version": "1.2.0",
"model_name": "LayoutModel",
"state": {
"_model_module": "@jupyter-widgets/base",
"_model_module_version": "1.2.0",
"_model_name": "LayoutModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "LayoutView",
"align_content": null,
"align_items": null,
"align_self": null,
"border": null,
"bottom": null,
"display": null,
"flex": null,
"flex_flow": null,
"grid_area": null,
"grid_auto_columns": null,
"grid_auto_flow": null,
"grid_auto_rows": null,
"grid_column": null,
"grid_gap": null,
"grid_row": null,
"grid_template_areas": null,
"grid_template_columns": null,
"grid_template_rows": null,
"height": null,
"justify_content": null,
"justify_items": null,
"left": null,
"margin": null,
"max_height": null,
"max_width": null,
"min_height": null,
"min_width": null,
"object_fit": null,
"object_position": null,
"order": null,
"overflow": null,
"overflow_x": null,
"overflow_y": null,
"padding": null,
"right": null,
"top": null,
"visibility": null,
"width": null
}
},
"9fee45523ded45d99517e718e1229408": {
"model_module": "@jupyter-widgets/base",
"model_module_version": "1.2.0",
"model_name": "LayoutModel",
"state": {
"_model_module": "@jupyter-widgets/base",
"_model_module_version": "1.2.0",
"_model_name": "LayoutModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "LayoutView",
"align_content": null,
"align_items": null,
"align_self": null,
"border": null,
"bottom": null,
"display": null,
"flex": null,
"flex_flow": null,
"grid_area": null,
"grid_auto_columns": null,
"grid_auto_flow": null,
"grid_auto_rows": null,
"grid_column": null,
"grid_gap": null,
"grid_row": null,
"grid_template_areas": null,
"grid_template_columns": null,
"grid_template_rows": null,
"height": null,
"justify_content": null,
"justify_items": null,
"left": null,
"margin": null,
"max_height": null,
"max_width": null,
"min_height": null,
"min_width": null,
"object_fit": null,
"object_position": null,
"order": null,
"overflow": null,
"overflow_x": null,
"overflow_y": null,
"padding": null,
"right": null,
"top": null,
"visibility": null,
"width": null
}
},
"a1b0289b4fb146a59b9a3cbf3d1960d0": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "FloatProgressModel",
"state": {
"_dom_classes": [],
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "FloatProgressModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/controls",
"_view_module_version": "1.5.0",
"_view_name": "ProgressView",
"bar_style": "success",
"description": "",
"description_tooltip": null,
"layout": "IPY_MODEL_9fee45523ded45d99517e718e1229408",
"max": 588,
"min": 0,
"orientation": "horizontal",
"style": "IPY_MODEL_ab0f71e2ef9543a799d270221b181e81",
"value": 588
}
},
"a1d2719d076145d8a88e101a53937596": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "HTMLModel",
"state": {
"_dom_classes": [],
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "HTMLModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/controls",
"_view_module_version": "1.5.0",
"_view_name": "HTMLView",
"description": "",
"description_tooltip": null,
"layout": "IPY_MODEL_9827853eb4ff417387631c3bc95e5d49",
"placeholder": "",
"style": "IPY_MODEL_db269406493e40ee9257aeb1d9256901",
"value": "tokenizer.model: 100%"
}
},
"a1f1649939a64ae6980283dece79934b": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "DescriptionStyleModel",
"state": {
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "DescriptionStyleModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "StyleView",
"description_width": ""
}
},
"a4ff849ee64f4acd8296a24d2370a25b": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "ProgressStyleModel",
"state": {
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "ProgressStyleModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "StyleView",
"bar_color": null,
"description_width": ""
}
},
"a597206990d34c50a27d7f818ec24648": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "HBoxModel",
"state": {
"_dom_classes": [],
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "HBoxModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/controls",
"_view_module_version": "1.5.0",
"_view_name": "HBoxView",
"box_style": "",
"children": [
"IPY_MODEL_7677cdddfa104dc9bdc352596fd57679",
"IPY_MODEL_dfa8f1e30c524bd9904de846bcb471df",
"IPY_MODEL_1703f1e2cede4393bdc5576aa28d8d26"
],
"layout": "IPY_MODEL_5b28753db78b45e3a083839ed0d71f17"
}
},
"a73546aa20c54fc6aa8e414ebd91a336": {
"model_module": "@jupyter-widgets/base",
"model_module_version": "1.2.0",
"model_name": "LayoutModel",
"state": {
"_model_module": "@jupyter-widgets/base",
"_model_module_version": "1.2.0",
"_model_name": "LayoutModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "LayoutView",
"align_content": null,
"align_items": null,
"align_self": null,
"border": null,
"bottom": null,
"display": null,
"flex": null,
"flex_flow": null,
"grid_area": null,
"grid_auto_columns": null,
"grid_auto_flow": null,
"grid_auto_rows": null,
"grid_column": null,
"grid_gap": null,
"grid_row": null,
"grid_template_areas": null,
"grid_template_columns": null,
"grid_template_rows": null,
"height": null,
"justify_content": null,
"justify_items": null,
"left": null,
"margin": null,
"max_height": null,
"max_width": null,
"min_height": null,
"min_width": null,
"object_fit": null,
"object_position": null,
"order": null,
"overflow": null,
"overflow_x": null,
"overflow_y": null,
"padding": null,
"right": null,
"top": null,
"visibility": null,
"width": null
}
},
"ab0f71e2ef9543a799d270221b181e81": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "ProgressStyleModel",
"state": {
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "ProgressStyleModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "StyleView",
"bar_color": null,
"description_width": ""
}
},
"ab25c4681afc4516acd2daf62c2e526b": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "HTMLModel",
"state": {
"_dom_classes": [],
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "HTMLModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/controls",
"_view_module_version": "1.5.0",
"_view_name": "HTMLView",
"description": "",
"description_tooltip": null,
"layout": "IPY_MODEL_722ae7185340428ea42f1f0322d11811",
"placeholder": "",
"style": "IPY_MODEL_6e394dc9bb584d7b84885265267f2174",
"value": "tokenizer.json: 100%"
}
},
"aba4df1d6c5b4fde90452a6d6241cb9f": {
"model_module": "@jupyter-widgets/base",
"model_module_version": "1.2.0",
"model_name": "LayoutModel",
"state": {
"_model_module": "@jupyter-widgets/base",
"_model_module_version": "1.2.0",
"_model_name": "LayoutModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "LayoutView",
"align_content": null,
"align_items": null,
"align_self": null,
"border": null,
"bottom": null,
"display": null,
"flex": null,
"flex_flow": null,
"grid_area": null,
"grid_auto_columns": null,
"grid_auto_flow": null,
"grid_auto_rows": null,
"grid_column": null,
"grid_gap": null,
"grid_row": null,
"grid_template_areas": null,
"grid_template_columns": null,
"grid_template_rows": null,
"height": null,
"justify_content": null,
"justify_items": null,
"left": null,
"margin": null,
"max_height": null,
"max_width": null,
"min_height": null,
"min_width": null,
"object_fit": null,
"object_position": null,
"order": null,
"overflow": null,
"overflow_x": null,
"overflow_y": null,
"padding": null,
"right": null,
"top": null,
"visibility": null,
"width": null
}
},
"abf15b1dd4f548229fdec015657aed73": {
"model_module": "@jupyter-widgets/base",
"model_module_version": "1.2.0",
"model_name": "LayoutModel",
"state": {
"_model_module": "@jupyter-widgets/base",
"_model_module_version": "1.2.0",
"_model_name": "LayoutModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "LayoutView",
"align_content": null,
"align_items": null,
"align_self": null,
"border": null,
"bottom": null,
"display": null,
"flex": null,
"flex_flow": null,
"grid_area": null,
"grid_auto_columns": null,
"grid_auto_flow": null,
"grid_auto_rows": null,
"grid_column": null,
"grid_gap": null,
"grid_row": null,
"grid_template_areas": null,
"grid_template_columns": null,
"grid_template_rows": null,
"height": null,
"justify_content": null,
"justify_items": null,
"left": null,
"margin": null,
"max_height": null,
"max_width": null,
"min_height": null,
"min_width": null,
"object_fit": null,
"object_position": null,
"order": null,
"overflow": null,
"overflow_x": null,
"overflow_y": null,
"padding": null,
"right": null,
"top": null,
"visibility": null,
"width": null
}
},
"ac0d0682ad7b48c0859b1fd3fe38f9a3": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "HTMLModel",
"state": {
"_dom_classes": [],
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "HTMLModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/controls",
"_view_module_version": "1.5.0",
"_view_name": "HTMLView",
"description": "",
"description_tooltip": null,
"layout": "IPY_MODEL_9ce97683d0d14b8682b88d297b05e1e8",
"placeholder": "",
"style": "IPY_MODEL_b2b5c455e3874760b0153297d85412fb",
"value": "Generating train split: 100%"
}
},
"ac2708c092394bdfbad40e65c5fcf5bd": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "HTMLModel",
"state": {
"_dom_classes": [],
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "HTMLModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/controls",
"_view_module_version": "1.5.0",
"_view_name": "HTMLView",
"description": "",
"description_tooltip": null,
"layout": "IPY_MODEL_cfc8db4601c241f5aa1664a2df9ad0a2",
"placeholder": "",
"style": "IPY_MODEL_025890c6531d450b9ad67861cff5eb66",
"value": " 4.14G/4.14G [00:21<00:00, 438MB/s]"
}
},
"ad4fc982db814395b18baa756ea16bc7": {
"model_module": "@jupyter-widgets/base",
"model_module_version": "1.2.0",
"model_name": "LayoutModel",
"state": {
"_model_module": "@jupyter-widgets/base",
"_model_module_version": "1.2.0",
"_model_name": "LayoutModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "LayoutView",
"align_content": null,
"align_items": null,
"align_self": null,
"border": null,
"bottom": null,
"display": null,
"flex": null,
"flex_flow": null,
"grid_area": null,
"grid_auto_columns": null,
"grid_auto_flow": null,
"grid_auto_rows": null,
"grid_column": null,
"grid_gap": null,
"grid_row": null,
"grid_template_areas": null,
"grid_template_columns": null,
"grid_template_rows": null,
"height": null,
"justify_content": null,
"justify_items": null,
"left": null,
"margin": null,
"max_height": null,
"max_width": null,
"min_height": null,
"min_width": null,
"object_fit": null,
"object_position": null,
"order": null,
"overflow": null,
"overflow_x": null,
"overflow_y": null,
"padding": null,
"right": null,
"top": null,
"visibility": null,
"width": null
}
},
"af4415d6ed8e4f149cbe55ad78640a8e": {
"model_module": "@jupyter-widgets/base",
"model_module_version": "1.2.0",
"model_name": "LayoutModel",
"state": {
"_model_module": "@jupyter-widgets/base",
"_model_module_version": "1.2.0",
"_model_name": "LayoutModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "LayoutView",
"align_content": null,
"align_items": null,
"align_self": null,
"border": null,
"bottom": null,
"display": null,
"flex": null,
"flex_flow": null,
"grid_area": null,
"grid_auto_columns": null,
"grid_auto_flow": null,
"grid_auto_rows": null,
"grid_column": null,
"grid_gap": null,
"grid_row": null,
"grid_template_areas": null,
"grid_template_columns": null,
"grid_template_rows": null,
"height": null,
"justify_content": null,
"justify_items": null,
"left": null,
"margin": null,
"max_height": null,
"max_width": null,
"min_height": null,
"min_width": null,
"object_fit": null,
"object_position": null,
"order": null,
"overflow": null,
"overflow_x": null,
"overflow_y": null,
"padding": null,
"right": null,
"top": null,
"visibility": null,
"width": null
}
},
"afb067fcfc1a4bc8aee1206e0e061100": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "HTMLModel",
"state": {
"_dom_classes": [],
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "HTMLModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/controls",
"_view_module_version": "1.5.0",
"_view_name": "HTMLView",
"description": "",
"description_tooltip": null,
"layout": "IPY_MODEL_b064befe0f57430ab07d62c18ea1b8e3",
"placeholder": "",
"style": "IPY_MODEL_c5d1c7b31fe044f5b4882b29c0c6948b",
"value": " 587k/587k [00:00<00:00, 16.4MB/s]"
}
},
"b064befe0f57430ab07d62c18ea1b8e3": {
"model_module": "@jupyter-widgets/base",
"model_module_version": "1.2.0",
"model_name": "LayoutModel",
"state": {
"_model_module": "@jupyter-widgets/base",
"_model_module_version": "1.2.0",
"_model_name": "LayoutModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "LayoutView",
"align_content": null,
"align_items": null,
"align_self": null,
"border": null,
"bottom": null,
"display": null,
"flex": null,
"flex_flow": null,
"grid_area": null,
"grid_auto_columns": null,
"grid_auto_flow": null,
"grid_auto_rows": null,
"grid_column": null,
"grid_gap": null,
"grid_row": null,
"grid_template_areas": null,
"grid_template_columns": null,
"grid_template_rows": null,
"height": null,
"justify_content": null,
"justify_items": null,
"left": null,
"margin": null,
"max_height": null,
"max_width": null,
"min_height": null,
"min_width": null,
"object_fit": null,
"object_position": null,
"order": null,
"overflow": null,
"overflow_x": null,
"overflow_y": null,
"padding": null,
"right": null,
"top": null,
"visibility": null,
"width": null
}
},
"b2b5c455e3874760b0153297d85412fb": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "DescriptionStyleModel",
"state": {
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "DescriptionStyleModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "StyleView",
"description_width": ""
}
},
"b36d3d2d9604420f8798330b296b61ee": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "FloatProgressModel",
"state": {
"_dom_classes": [],
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "FloatProgressModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/controls",
"_view_module_version": "1.5.0",
"_view_name": "ProgressView",
"bar_style": "success",
"description": "",
"description_tooltip": null,
"layout": "IPY_MODEL_ad4fc982db814395b18baa756ea16bc7",
"max": 172026,
"min": 0,
"orientation": "horizontal",
"style": "IPY_MODEL_d2525b5577a6425f8c77d66c12c76cc1",
"value": 172026
}
},
"b37374a767fc41c2b9e354f7cb11a802": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "HTMLModel",
"state": {
"_dom_classes": [],
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "HTMLModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/controls",
"_view_module_version": "1.5.0",
"_view_name": "HTMLView",
"description": "",
"description_tooltip": null,
"layout": "IPY_MODEL_04405d46d02d4d9d9cafcd1a47f18b19",
"placeholder": "",
"style": "IPY_MODEL_0301b3c2076c4e158e8f5af6ce74df77",
"value": "Map: 100%"
}
},
"b394d711ae9242c788265f24c9a5ee42": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "HBoxModel",
"state": {
"_dom_classes": [],
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "HBoxModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/controls",
"_view_module_version": "1.5.0",
"_view_name": "HBoxView",
"box_style": "",
"children": [
"IPY_MODEL_b416ab6b52f3458fac03d62c44ff70c3",
"IPY_MODEL_a1b0289b4fb146a59b9a3cbf3d1960d0",
"IPY_MODEL_17b0a9fada8c402f90f7ab8ac3f84006"
],
"layout": "IPY_MODEL_0994869c36a4402fa6bb0391c28027e0"
}
},
"b416ab6b52f3458fac03d62c44ff70c3": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "HTMLModel",
"state": {
"_dom_classes": [],
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "HTMLModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/controls",
"_view_module_version": "1.5.0",
"_view_name": "HTMLView",
"description": "",
"description_tooltip": null,
"layout": "IPY_MODEL_635701e66e4f44b39ee094f1e3953af9",
"placeholder": "",
"style": "IPY_MODEL_f5537922d4e94925a118b4102e1b5db3",
"value": "README.md: 100%"
}
},
"b4c1a2579601463eae261e9d8d519658": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "HTMLModel",
"state": {
"_dom_classes": [],
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "HTMLModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/controls",
"_view_module_version": "1.5.0",
"_view_name": "HTMLView",
"description": "",
"description_tooltip": null,
"layout": "IPY_MODEL_ce48b32b9ad24145814ae20bfd91b56d",
"placeholder": "",
"style": "IPY_MODEL_9c4f0814b946400c8d35d973a8907f8a",
"value": "generation_config.json: 100%"
}
},
"b7183b3341c34670aacfd32ec049ac25": {
"model_module": "@jupyter-widgets/base",
"model_module_version": "1.2.0",
"model_name": "LayoutModel",
"state": {
"_model_module": "@jupyter-widgets/base",
"_model_module_version": "1.2.0",
"_model_name": "LayoutModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "LayoutView",
"align_content": null,
"align_items": null,
"align_self": null,
"border": null,
"bottom": null,
"display": null,
"flex": null,
"flex_flow": null,
"grid_area": null,
"grid_auto_columns": null,
"grid_auto_flow": null,
"grid_auto_rows": null,
"grid_column": null,
"grid_gap": null,
"grid_row": null,
"grid_template_areas": null,
"grid_template_columns": null,
"grid_template_rows": null,
"height": null,
"justify_content": null,
"justify_items": null,
"left": null,
"margin": null,
"max_height": null,
"max_width": null,
"min_height": null,
"min_width": null,
"object_fit": null,
"object_position": null,
"order": null,
"overflow": null,
"overflow_x": null,
"overflow_y": null,
"padding": null,
"right": null,
"top": null,
"visibility": null,
"width": null
}
},
"b79b90dfab6340b19cd27f40c497420d": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "HTMLModel",
"state": {
"_dom_classes": [],
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "HTMLModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/controls",
"_view_module_version": "1.5.0",
"_view_name": "HTMLView",
"description": "",
"description_tooltip": null,
"layout": "IPY_MODEL_c5f5ed3035a54779ac1d2c5c7743ab6d",
"placeholder": "",
"style": "IPY_MODEL_730d88a3a02e4b528efd0b7a5b4bbe51",
"value": " 157/157 [00:00<00:00, 6.43kB/s]"
}
},
"b7b47d22e60b4f70bcab335bccc016f7": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "DescriptionStyleModel",
"state": {
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "DescriptionStyleModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "StyleView",
"description_width": ""
}
},
"b882d5d3ca8442aaa2ddef15e47e5b45": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "ProgressStyleModel",
"state": {
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "ProgressStyleModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "StyleView",
"bar_color": null,
"description_width": ""
}
},
"ba699d43cb8f431b92a45858f6f0f6a5": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "ProgressStyleModel",
"state": {
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "ProgressStyleModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "StyleView",
"bar_color": null,
"description_width": ""
}
},
"bc13c65b38ed4653ab3f9a99d861f4dc": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "DescriptionStyleModel",
"state": {
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "DescriptionStyleModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "StyleView",
"description_width": ""
}
},
"bcfa0a1a0022496e850f1d44cac0532b": {
"model_module": "@jupyter-widgets/base",
"model_module_version": "1.2.0",
"model_name": "LayoutModel",
"state": {
"_model_module": "@jupyter-widgets/base",
"_model_module_version": "1.2.0",
"_model_name": "LayoutModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "LayoutView",
"align_content": null,
"align_items": null,
"align_self": null,
"border": null,
"bottom": null,
"display": null,
"flex": null,
"flex_flow": null,
"grid_area": null,
"grid_auto_columns": null,
"grid_auto_flow": null,
"grid_auto_rows": null,
"grid_column": null,
"grid_gap": null,
"grid_row": null,
"grid_template_areas": null,
"grid_template_columns": null,
"grid_template_rows": null,
"height": null,
"justify_content": null,
"justify_items": null,
"left": null,
"margin": null,
"max_height": null,
"max_width": null,
"min_height": null,
"min_width": null,
"object_fit": null,
"object_position": null,
"order": null,
"overflow": null,
"overflow_x": null,
"overflow_y": null,
"padding": null,
"right": null,
"top": null,
"visibility": null,
"width": null
}
},
"bd47b355ee6b45b681d0a03162e0872e": {
"model_module": "@jupyter-widgets/base",
"model_module_version": "1.2.0",
"model_name": "LayoutModel",
"state": {
"_model_module": "@jupyter-widgets/base",
"_model_module_version": "1.2.0",
"_model_name": "LayoutModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "LayoutView",
"align_content": null,
"align_items": null,
"align_self": null,
"border": null,
"bottom": null,
"display": null,
"flex": null,
"flex_flow": null,
"grid_area": null,
"grid_auto_columns": null,
"grid_auto_flow": null,
"grid_auto_rows": null,
"grid_column": null,
"grid_gap": null,
"grid_row": null,
"grid_template_areas": null,
"grid_template_columns": null,
"grid_template_rows": null,
"height": null,
"justify_content": null,
"justify_items": null,
"left": null,
"margin": null,
"max_height": null,
"max_width": null,
"min_height": null,
"min_width": null,
"object_fit": null,
"object_position": null,
"order": null,
"overflow": null,
"overflow_x": null,
"overflow_y": null,
"padding": null,
"right": null,
"top": null,
"visibility": null,
"width": null
}
},
"be112d605e874960b57620ab725742c1": {
"model_module": "@jupyter-widgets/base",
"model_module_version": "1.2.0",
"model_name": "LayoutModel",
"state": {
"_model_module": "@jupyter-widgets/base",
"_model_module_version": "1.2.0",
"_model_name": "LayoutModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "LayoutView",
"align_content": null,
"align_items": null,
"align_self": null,
"border": null,
"bottom": null,
"display": null,
"flex": null,
"flex_flow": null,
"grid_area": null,
"grid_auto_columns": null,
"grid_auto_flow": null,
"grid_auto_rows": null,
"grid_column": null,
"grid_gap": null,
"grid_row": null,
"grid_template_areas": null,
"grid_template_columns": null,
"grid_template_rows": null,
"height": null,
"justify_content": null,
"justify_items": null,
"left": null,
"margin": null,
"max_height": null,
"max_width": null,
"min_height": null,
"min_width": null,
"object_fit": null,
"object_position": null,
"order": null,
"overflow": null,
"overflow_x": null,
"overflow_y": null,
"padding": null,
"right": null,
"top": null,
"visibility": null,
"width": null
}
},
"bff66c38b69e4641865a4cbb532f47c1": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "DescriptionStyleModel",
"state": {
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "DescriptionStyleModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "StyleView",
"description_width": ""
}
},
"c3f26313e34440e0918dc5e6c53fe256": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "HBoxModel",
"state": {
"_dom_classes": [],
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "HBoxModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/controls",
"_view_module_version": "1.5.0",
"_view_name": "HBoxView",
"box_style": "",
"children": [
"IPY_MODEL_517365223084483a8d8b59410c6fe95a",
"IPY_MODEL_da6c2c2731cb4709a271bca5478a245d",
"IPY_MODEL_6dba4a23cf4547adb17eaf446eef7297"
],
"layout": "IPY_MODEL_67793453c68943329ccd77c0b5200f2a"
}
},
"c45929291edb45db829d6bf4caeb3cc7": {
"model_module": "@jupyter-widgets/base",
"model_module_version": "1.2.0",
"model_name": "LayoutModel",
"state": {
"_model_module": "@jupyter-widgets/base",
"_model_module_version": "1.2.0",
"_model_name": "LayoutModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "LayoutView",
"align_content": null,
"align_items": null,
"align_self": null,
"border": null,
"bottom": null,
"display": null,
"flex": null,
"flex_flow": null,
"grid_area": null,
"grid_auto_columns": null,
"grid_auto_flow": null,
"grid_auto_rows": null,
"grid_column": null,
"grid_gap": null,
"grid_row": null,
"grid_template_areas": null,
"grid_template_columns": null,
"grid_template_rows": null,
"height": null,
"justify_content": null,
"justify_items": null,
"left": null,
"margin": null,
"max_height": null,
"max_width": null,
"min_height": null,
"min_width": null,
"object_fit": null,
"object_position": null,
"order": null,
"overflow": null,
"overflow_x": null,
"overflow_y": null,
"padding": null,
"right": null,
"top": null,
"visibility": null,
"width": null
}
},
"c5d1c7b31fe044f5b4882b29c0c6948b": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "DescriptionStyleModel",
"state": {
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "DescriptionStyleModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "StyleView",
"description_width": ""
}
},
"c5e622547fb048128d67240d16152f79": {
"model_module": "@jupyter-widgets/base",
"model_module_version": "1.2.0",
"model_name": "LayoutModel",
"state": {
"_model_module": "@jupyter-widgets/base",
"_model_module_version": "1.2.0",
"_model_name": "LayoutModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "LayoutView",
"align_content": null,
"align_items": null,
"align_self": null,
"border": null,
"bottom": null,
"display": null,
"flex": null,
"flex_flow": null,
"grid_area": null,
"grid_auto_columns": null,
"grid_auto_flow": null,
"grid_auto_rows": null,
"grid_column": null,
"grid_gap": null,
"grid_row": null,
"grid_template_areas": null,
"grid_template_columns": null,
"grid_template_rows": null,
"height": null,
"justify_content": null,
"justify_items": null,
"left": null,
"margin": null,
"max_height": null,
"max_width": null,
"min_height": null,
"min_width": null,
"object_fit": null,
"object_position": null,
"order": null,
"overflow": null,
"overflow_x": null,
"overflow_y": null,
"padding": null,
"right": null,
"top": null,
"visibility": null,
"width": null
}
},
"c5f5ed3035a54779ac1d2c5c7743ab6d": {
"model_module": "@jupyter-widgets/base",
"model_module_version": "1.2.0",
"model_name": "LayoutModel",
"state": {
"_model_module": "@jupyter-widgets/base",
"_model_module_version": "1.2.0",
"_model_name": "LayoutModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "LayoutView",
"align_content": null,
"align_items": null,
"align_self": null,
"border": null,
"bottom": null,
"display": null,
"flex": null,
"flex_flow": null,
"grid_area": null,
"grid_auto_columns": null,
"grid_auto_flow": null,
"grid_auto_rows": null,
"grid_column": null,
"grid_gap": null,
"grid_row": null,
"grid_template_areas": null,
"grid_template_columns": null,
"grid_template_rows": null,
"height": null,
"justify_content": null,
"justify_items": null,
"left": null,
"margin": null,
"max_height": null,
"max_width": null,
"min_height": null,
"min_width": null,
"object_fit": null,
"object_position": null,
"order": null,
"overflow": null,
"overflow_x": null,
"overflow_y": null,
"padding": null,
"right": null,
"top": null,
"visibility": null,
"width": null
}
},
"c70ca67cf8074d389200b28c96c41c86": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "HBoxModel",
"state": {
"_dom_classes": [],
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "HBoxModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/controls",
"_view_module_version": "1.5.0",
"_view_name": "HBoxView",
"box_style": "",
"children": [
"IPY_MODEL_b37374a767fc41c2b9e354f7cb11a802",
"IPY_MODEL_b36d3d2d9604420f8798330b296b61ee",
"IPY_MODEL_7040bb77fe904a378382fb8f0bb3ac3f"
],
"layout": "IPY_MODEL_232edccc247f40afb3aaf4458a45c084"
}
},
"c8509c42f414476e8ff36ca377a9b062": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "DescriptionStyleModel",
"state": {
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "DescriptionStyleModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "StyleView",
"description_width": ""
}
},
"c9a42afb532542c78e86ff4618406c47": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "DescriptionStyleModel",
"state": {
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "DescriptionStyleModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "StyleView",
"description_width": ""
}
},
"cd7d8e06b17c458593aba91e9981acd5": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "HTMLModel",
"state": {
"_dom_classes": [],
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "HTMLModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/controls",
"_view_module_version": "1.5.0",
"_view_name": "HTMLView",
"description": "",
"description_tooltip": null,
"layout": "IPY_MODEL_7d7f3cdde6e7482580883140dd1ba3ee",
"placeholder": "",
"style": "IPY_MODEL_467cef144dbd4d99bb1f5111c8ca25fa",
"value": " 450/450 [00:00<00:00, 10.5kB/s]"
}
},
"cde99f9f0c26432fbf9c34ee12f04852": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "FloatProgressModel",
"state": {
"_dom_classes": [],
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "FloatProgressModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/controls",
"_view_module_version": "1.5.0",
"_view_name": "ProgressView",
"bar_style": "success",
"description": "",
"description_tooltip": null,
"layout": "IPY_MODEL_9eeec3eb1b384a51b606d71e8ad9a171",
"max": 7702564736,
"min": 0,
"orientation": "horizontal",
"style": "IPY_MODEL_ba699d43cb8f431b92a45858f6f0f6a5",
"value": 7702564736
}
},
"ce48b32b9ad24145814ae20bfd91b56d": {
"model_module": "@jupyter-widgets/base",
"model_module_version": "1.2.0",
"model_name": "LayoutModel",
"state": {
"_model_module": "@jupyter-widgets/base",
"_model_module_version": "1.2.0",
"_model_name": "LayoutModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "LayoutView",
"align_content": null,
"align_items": null,
"align_self": null,
"border": null,
"bottom": null,
"display": null,
"flex": null,
"flex_flow": null,
"grid_area": null,
"grid_auto_columns": null,
"grid_auto_flow": null,
"grid_auto_rows": null,
"grid_column": null,
"grid_gap": null,
"grid_row": null,
"grid_template_areas": null,
"grid_template_columns": null,
"grid_template_rows": null,
"height": null,
"justify_content": null,
"justify_items": null,
"left": null,
"margin": null,
"max_height": null,
"max_width": null,
"min_height": null,
"min_width": null,
"object_fit": null,
"object_position": null,
"order": null,
"overflow": null,
"overflow_x": null,
"overflow_y": null,
"padding": null,
"right": null,
"top": null,
"visibility": null,
"width": null
}
},
"cec0767678744a81a457f9bfa2287e92": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "ProgressStyleModel",
"state": {
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "ProgressStyleModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "StyleView",
"bar_color": null,
"description_width": ""
}
},
"cef6b12b6552416ba87bdecf578c190f": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "HBoxModel",
"state": {
"_dom_classes": [],
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "HBoxModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/controls",
"_view_module_version": "1.5.0",
"_view_name": "HBoxView",
"box_style": "",
"children": [
"IPY_MODEL_02426c5157ef4c92b1f912a2078032d6",
"IPY_MODEL_86dc1f03a7384d7b926c83ba9ad67625",
"IPY_MODEL_cd7d8e06b17c458593aba91e9981acd5"
],
"layout": "IPY_MODEL_e4f0ba3f0d6a487db87859777110804f"
}
},
"cfc8db4601c241f5aa1664a2df9ad0a2": {
"model_module": "@jupyter-widgets/base",
"model_module_version": "1.2.0",
"model_name": "LayoutModel",
"state": {
"_model_module": "@jupyter-widgets/base",
"_model_module_version": "1.2.0",
"_model_name": "LayoutModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "LayoutView",
"align_content": null,
"align_items": null,
"align_self": null,
"border": null,
"bottom": null,
"display": null,
"flex": null,
"flex_flow": null,
"grid_area": null,
"grid_auto_columns": null,
"grid_auto_flow": null,
"grid_auto_rows": null,
"grid_column": null,
"grid_gap": null,
"grid_row": null,
"grid_template_areas": null,
"grid_template_columns": null,
"grid_template_rows": null,
"height": null,
"justify_content": null,
"justify_items": null,
"left": null,
"margin": null,
"max_height": null,
"max_width": null,
"min_height": null,
"min_width": null,
"object_fit": null,
"object_position": null,
"order": null,
"overflow": null,
"overflow_x": null,
"overflow_y": null,
"padding": null,
"right": null,
"top": null,
"visibility": null,
"width": null
}
},
"d02ed9830c494a59a67c1e95c2b684bd": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "HBoxModel",
"state": {
"_dom_classes": [],
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "HBoxModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/controls",
"_view_module_version": "1.5.0",
"_view_name": "HBoxView",
"box_style": "",
"children": [
"IPY_MODEL_7e0bca45410b467c92f97deaaf153ce6",
"IPY_MODEL_16f2c1312876443784df678b0fe424b1",
"IPY_MODEL_1480812645954012a9dc22049f1295a5"
],
"layout": "IPY_MODEL_856c8aab5f8e451ebc7e19e79105ed0b"
}
},
"d143438a3e574a78be2e052dc6dae33d": {
"model_module": "@jupyter-widgets/base",
"model_module_version": "1.2.0",
"model_name": "LayoutModel",
"state": {
"_model_module": "@jupyter-widgets/base",
"_model_module_version": "1.2.0",
"_model_name": "LayoutModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "LayoutView",
"align_content": null,
"align_items": null,
"align_self": null,
"border": null,
"bottom": null,
"display": null,
"flex": null,
"flex_flow": null,
"grid_area": null,
"grid_auto_columns": null,
"grid_auto_flow": null,
"grid_auto_rows": null,
"grid_column": null,
"grid_gap": null,
"grid_row": null,
"grid_template_areas": null,
"grid_template_columns": null,
"grid_template_rows": null,
"height": null,
"justify_content": null,
"justify_items": null,
"left": null,
"margin": null,
"max_height": null,
"max_width": null,
"min_height": null,
"min_width": null,
"object_fit": null,
"object_position": null,
"order": null,
"overflow": null,
"overflow_x": null,
"overflow_y": null,
"padding": null,
"right": null,
"top": null,
"visibility": null,
"width": null
}
},
"d2176f04c91a4bc5ba031980c22e5b99": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "ProgressStyleModel",
"state": {
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "ProgressStyleModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "StyleView",
"bar_color": null,
"description_width": ""
}
},
"d2525b5577a6425f8c77d66c12c76cc1": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "ProgressStyleModel",
"state": {
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "ProgressStyleModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "StyleView",
"bar_color": null,
"description_width": ""
}
},
"d38ace4d6758421f8ac21b5317a90cda": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "HBoxModel",
"state": {
"_dom_classes": [],
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "HBoxModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/controls",
"_view_module_version": "1.5.0",
"_view_name": "HBoxView",
"box_style": "",
"children": [
"IPY_MODEL_ab25c4681afc4516acd2daf62c2e526b",
"IPY_MODEL_fd706226b91847a39fc3dde16df4ce9d",
"IPY_MODEL_3f47030858274683b8b14ad06cc8c0d5"
],
"layout": "IPY_MODEL_252c63f990844e079f30f825d2c07184"
}
},
"d6f1a54080fe47699cff262103aa3c5a": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "FloatProgressModel",
"state": {
"_dom_classes": [],
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "FloatProgressModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/controls",
"_view_module_version": "1.5.0",
"_view_name": "ProgressView",
"bar_style": "success",
"description": "",
"description_tooltip": null,
"layout": "IPY_MODEL_54205208826b40d28f6387784198101a",
"max": 1,
"min": 0,
"orientation": "horizontal",
"style": "IPY_MODEL_4fb5a1222abd43c885f6d4e38f80ccf2",
"value": 1
}
},
"d75e04ea7c4644a3a3390b98284eb71e": {
"model_module": "@jupyter-widgets/base",
"model_module_version": "1.2.0",
"model_name": "LayoutModel",
"state": {
"_model_module": "@jupyter-widgets/base",
"_model_module_version": "1.2.0",
"_model_name": "LayoutModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "LayoutView",
"align_content": null,
"align_items": null,
"align_self": null,
"border": null,
"bottom": null,
"display": null,
"flex": null,
"flex_flow": null,
"grid_area": null,
"grid_auto_columns": null,
"grid_auto_flow": null,
"grid_auto_rows": null,
"grid_column": null,
"grid_gap": null,
"grid_row": null,
"grid_template_areas": null,
"grid_template_columns": null,
"grid_template_rows": null,
"height": null,
"justify_content": null,
"justify_items": null,
"left": null,
"margin": null,
"max_height": null,
"max_width": null,
"min_height": null,
"min_width": null,
"object_fit": null,
"object_position": null,
"order": null,
"overflow": null,
"overflow_x": null,
"overflow_y": null,
"padding": null,
"right": null,
"top": null,
"visibility": null,
"width": null
}
},
"da6c2c2731cb4709a271bca5478a245d": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "FloatProgressModel",
"state": {
"_dom_classes": [],
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "FloatProgressModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/controls",
"_view_module_version": "1.5.0",
"_view_name": "ProgressView",
"bar_style": "success",
"description": "",
"description_tooltip": null,
"layout": "IPY_MODEL_ef2bd43356e547c8b6813308b61eab04",
"max": 136734,
"min": 0,
"orientation": "horizontal",
"style": "IPY_MODEL_3c9e9bb23c054fc8b9f3a6658e8d5a40",
"value": 136734
}
},
"db269406493e40ee9257aeb1d9256901": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "DescriptionStyleModel",
"state": {
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "DescriptionStyleModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "StyleView",
"description_width": ""
}
},
"dcbe29b4ad914c36be45549a87712136": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "FloatProgressModel",
"state": {
"_dom_classes": [],
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "FloatProgressModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/controls",
"_view_module_version": "1.5.0",
"_view_name": "ProgressView",
"bar_style": "success",
"description": "",
"description_tooltip": null,
"layout": "IPY_MODEL_406e55d150d54f9db3f324e487e3aae9",
"max": 172026,
"min": 0,
"orientation": "horizontal",
"style": "IPY_MODEL_d2176f04c91a4bc5ba031980c22e5b99",
"value": 172026
}
},
"dfa8f1e30c524bd9904de846bcb471df": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "FloatProgressModel",
"state": {
"_dom_classes": [],
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "FloatProgressModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/controls",
"_view_module_version": "1.5.0",
"_view_name": "ProgressView",
"bar_style": "success",
"description": "",
"description_tooltip": null,
"layout": "IPY_MODEL_d143438a3e574a78be2e052dc6dae33d",
"max": 167832240,
"min": 0,
"orientation": "horizontal",
"style": "IPY_MODEL_34172978ed324047b813e6c42f5d8930",
"value": 167832240
}
},
"e13f629d29b0413985598507411192a3": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "ProgressStyleModel",
"state": {
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "ProgressStyleModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "StyleView",
"bar_color": null,
"description_width": ""
}
},
"e202f31c8f854fa19844b176bc2917c2": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "HTMLModel",
"state": {
"_dom_classes": [],
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "HTMLModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/controls",
"_view_module_version": "1.5.0",
"_view_name": "HTMLView",
"description": "",
"description_tooltip": null,
"layout": "IPY_MODEL_f7c0f25f2e3b4b81bc8c7c65fa65ba65",
"placeholder": "",
"style": "IPY_MODEL_7bb43fd56e754302bbe77c083996fa97",
"value": "Map (num_proc=2): 100%"
}
},
"e26f854045484cd7a78f4df5b2e2bdc5": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "DescriptionStyleModel",
"state": {
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "DescriptionStyleModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "StyleView",
"description_width": ""
}
},
"e4f0ba3f0d6a487db87859777110804f": {
"model_module": "@jupyter-widgets/base",
"model_module_version": "1.2.0",
"model_name": "LayoutModel",
"state": {
"_model_module": "@jupyter-widgets/base",
"_model_module_version": "1.2.0",
"_model_name": "LayoutModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "LayoutView",
"align_content": null,
"align_items": null,
"align_self": null,
"border": null,
"bottom": null,
"display": null,
"flex": null,
"flex_flow": null,
"grid_area": null,
"grid_auto_columns": null,
"grid_auto_flow": null,
"grid_auto_rows": null,
"grid_column": null,
"grid_gap": null,
"grid_row": null,
"grid_template_areas": null,
"grid_template_columns": null,
"grid_template_rows": null,
"height": null,
"justify_content": null,
"justify_items": null,
"left": null,
"margin": null,
"max_height": null,
"max_width": null,
"min_height": null,
"min_width": null,
"object_fit": null,
"object_position": null,
"order": null,
"overflow": null,
"overflow_x": null,
"overflow_y": null,
"padding": null,
"right": null,
"top": null,
"visibility": null,
"width": null
}
},
"e82aa85c090e40b199df04e9761c0867": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "HTMLModel",
"state": {
"_dom_classes": [],
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "HTMLModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/controls",
"_view_module_version": "1.5.0",
"_view_name": "HTMLView",
"description": "",
"description_tooltip": null,
"layout": "IPY_MODEL_0d91e0c88db442e9a5f74d66c75fe33a",
"placeholder": "",
"style": "IPY_MODEL_8e2ad3625e624f7ba3ade89be147652d",
"value": "train-00001-of-00002.parquet: 100%"
}
},
"e9461ce46eb3437e8181e7d87031e048": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "HTMLModel",
"state": {
"_dom_classes": [],
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "HTMLModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/controls",
"_view_module_version": "1.5.0",
"_view_name": "HTMLView",
"description": "",
"description_tooltip": null,
"layout": "IPY_MODEL_62e5a5dea5fe404fb6b54561b17dfed2",
"placeholder": "",
"style": "IPY_MODEL_eaca2be4971344d6b56dcf64c3a69a8e",
"value": " 158M/158M [00:01<00:00, 184MB/s]"
}
},
"e9755d20f6cb4674b0bc6adb6da5015d": {
"model_module": "@jupyter-widgets/base",
"model_module_version": "1.2.0",
"model_name": "LayoutModel",
"state": {
"_model_module": "@jupyter-widgets/base",
"_model_module_version": "1.2.0",
"_model_name": "LayoutModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "LayoutView",
"align_content": null,
"align_items": null,
"align_self": null,
"border": null,
"bottom": null,
"display": null,
"flex": null,
"flex_flow": null,
"grid_area": null,
"grid_auto_columns": null,
"grid_auto_flow": null,
"grid_auto_rows": null,
"grid_column": null,
"grid_gap": null,
"grid_row": null,
"grid_template_areas": null,
"grid_template_columns": null,
"grid_template_rows": null,
"height": null,
"justify_content": null,
"justify_items": null,
"left": null,
"margin": null,
"max_height": null,
"max_width": null,
"min_height": null,
"min_width": null,
"object_fit": null,
"object_position": null,
"order": null,
"overflow": null,
"overflow_x": null,
"overflow_y": null,
"padding": null,
"right": null,
"top": null,
"visibility": null,
"width": null
}
},
"eaca2be4971344d6b56dcf64c3a69a8e": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "DescriptionStyleModel",
"state": {
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "DescriptionStyleModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "StyleView",
"description_width": ""
}
},
"ee1700276c2c4f36a391c9c64606d5a6": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "HBoxModel",
"state": {
"_dom_classes": [],
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "HBoxModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/controls",
"_view_module_version": "1.5.0",
"_view_name": "HBoxView",
"box_style": "",
"children": [
"IPY_MODEL_ac0d0682ad7b48c0859b1fd3fe38f9a3",
"IPY_MODEL_dcbe29b4ad914c36be45549a87712136",
"IPY_MODEL_4c00184bff2b4f61a8b2b0866948bab0"
],
"layout": "IPY_MODEL_31b710c446a04859bb1bc068b9c42bcc"
}
},
"ef2bd43356e547c8b6813308b61eab04": {
"model_module": "@jupyter-widgets/base",
"model_module_version": "1.2.0",
"model_name": "LayoutModel",
"state": {
"_model_module": "@jupyter-widgets/base",
"_model_module_version": "1.2.0",
"_model_name": "LayoutModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "LayoutView",
"align_content": null,
"align_items": null,
"align_self": null,
"border": null,
"bottom": null,
"display": null,
"flex": null,
"flex_flow": null,
"grid_area": null,
"grid_auto_columns": null,
"grid_auto_flow": null,
"grid_auto_rows": null,
"grid_column": null,
"grid_gap": null,
"grid_row": null,
"grid_template_areas": null,
"grid_template_columns": null,
"grid_template_rows": null,
"height": null,
"justify_content": null,
"justify_items": null,
"left": null,
"margin": null,
"max_height": null,
"max_width": null,
"min_height": null,
"min_width": null,
"object_fit": null,
"object_position": null,
"order": null,
"overflow": null,
"overflow_x": null,
"overflow_y": null,
"padding": null,
"right": null,
"top": null,
"visibility": null,
"width": null
}
},
"f288ceb6bc954b9cab4113f679266350": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "HTMLModel",
"state": {
"_dom_classes": [],
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "HTMLModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/controls",
"_view_module_version": "1.5.0",
"_view_name": "HTMLView",
"description": "",
"description_tooltip": null,
"layout": "IPY_MODEL_b7183b3341c34670aacfd32ec049ac25",
"placeholder": "",
"style": "IPY_MODEL_93538debadaf4cad9b3563ea1b7c7e74",
"value": " 587k/587k [00:01<00:00, 454kB/s]"
}
},
"f4087fc8d18c4b9f8edf648f812f4b40": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "HBoxModel",
"state": {
"_dom_classes": [],
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "HBoxModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/controls",
"_view_module_version": "1.5.0",
"_view_name": "HBoxView",
"box_style": "",
"children": [
"IPY_MODEL_0e8b4643c42a462d90cbddd169fbb17b",
"IPY_MODEL_d6f1a54080fe47699cff262103aa3c5a",
"IPY_MODEL_4f98983f315f498981f5aa4de015076e"
],
"layout": "IPY_MODEL_9c3c23ca3aab4f72ba94c8dc769d8e92"
}
},
"f4334c21a9d24e48b43232cce101e395": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "HBoxModel",
"state": {
"_dom_classes": [],
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "HBoxModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/controls",
"_view_module_version": "1.5.0",
"_view_name": "HBoxView",
"box_style": "",
"children": [
"IPY_MODEL_38b7d7231e3a4b078ff15c0af7d4bab6",
"IPY_MODEL_3f3b84e262d744558b132ac31da96081",
"IPY_MODEL_afb067fcfc1a4bc8aee1206e0e061100"
],
"layout": "IPY_MODEL_fad80247656042788748ea5c5c9f64df"
}
},
"f4cde1cee7034425a60ecad0b5c07dda": {
"model_module": "@jupyter-widgets/base",
"model_module_version": "1.2.0",
"model_name": "LayoutModel",
"state": {
"_model_module": "@jupyter-widgets/base",
"_model_module_version": "1.2.0",
"_model_name": "LayoutModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "LayoutView",
"align_content": null,
"align_items": null,
"align_self": null,
"border": null,
"bottom": null,
"display": null,
"flex": null,
"flex_flow": null,
"grid_area": null,
"grid_auto_columns": null,
"grid_auto_flow": null,
"grid_auto_rows": null,
"grid_column": null,
"grid_gap": null,
"grid_row": null,
"grid_template_areas": null,
"grid_template_columns": null,
"grid_template_rows": null,
"height": null,
"justify_content": null,
"justify_items": null,
"left": null,
"margin": null,
"max_height": null,
"max_width": null,
"min_height": null,
"min_width": null,
"object_fit": null,
"object_position": null,
"order": null,
"overflow": null,
"overflow_x": null,
"overflow_y": null,
"padding": null,
"right": null,
"top": null,
"visibility": null,
"width": null
}
},
"f5537922d4e94925a118b4102e1b5db3": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "DescriptionStyleModel",
"state": {
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "DescriptionStyleModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "StyleView",
"description_width": ""
}
},
"f61217d62cf94257b6cc9673d8e6cab1": {
"model_module": "@jupyter-widgets/base",
"model_module_version": "1.2.0",
"model_name": "LayoutModel",
"state": {
"_model_module": "@jupyter-widgets/base",
"_model_module_version": "1.2.0",
"_model_name": "LayoutModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "LayoutView",
"align_content": null,
"align_items": null,
"align_self": null,
"border": null,
"bottom": null,
"display": null,
"flex": null,
"flex_flow": null,
"grid_area": null,
"grid_auto_columns": null,
"grid_auto_flow": null,
"grid_auto_rows": null,
"grid_column": null,
"grid_gap": null,
"grid_row": null,
"grid_template_areas": null,
"grid_template_columns": null,
"grid_template_rows": null,
"height": null,
"justify_content": null,
"justify_items": null,
"left": null,
"margin": null,
"max_height": null,
"max_width": null,
"min_height": null,
"min_width": null,
"object_fit": null,
"object_position": null,
"order": null,
"overflow": null,
"overflow_x": null,
"overflow_y": null,
"padding": null,
"right": null,
"top": null,
"visibility": null,
"width": null
}
},
"f73f729c27414608b106a61357ef1f9b": {
"model_module": "@jupyter-widgets/base",
"model_module_version": "1.2.0",
"model_name": "LayoutModel",
"state": {
"_model_module": "@jupyter-widgets/base",
"_model_module_version": "1.2.0",
"_model_name": "LayoutModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "LayoutView",
"align_content": null,
"align_items": null,
"align_self": null,
"border": null,
"bottom": null,
"display": null,
"flex": null,
"flex_flow": null,
"grid_area": null,
"grid_auto_columns": null,
"grid_auto_flow": null,
"grid_auto_rows": null,
"grid_column": null,
"grid_gap": null,
"grid_row": null,
"grid_template_areas": null,
"grid_template_columns": null,
"grid_template_rows": null,
"height": null,
"justify_content": null,
"justify_items": null,
"left": null,
"margin": null,
"max_height": null,
"max_width": null,
"min_height": null,
"min_width": null,
"object_fit": null,
"object_position": null,
"order": null,
"overflow": null,
"overflow_x": null,
"overflow_y": null,
"padding": null,
"right": null,
"top": null,
"visibility": null,
"width": null
}
},
"f751fcf5656b4240a576a0f4f309c51f": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "HTMLModel",
"state": {
"_dom_classes": [],
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "HTMLModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/controls",
"_view_module_version": "1.5.0",
"_view_name": "HTMLView",
"description": "",
"description_tooltip": null,
"layout": "IPY_MODEL_528b64da057d43c395ff2ce1147a8576",
"placeholder": "",
"style": "IPY_MODEL_6894219580074769999b672cb6e677cd",
"value": " 1/1 [01:08<00:00, 68.28s/it]"
}
},
"f7c0f25f2e3b4b81bc8c7c65fa65ba65": {
"model_module": "@jupyter-widgets/base",
"model_module_version": "1.2.0",
"model_name": "LayoutModel",
"state": {
"_model_module": "@jupyter-widgets/base",
"_model_module_version": "1.2.0",
"_model_name": "LayoutModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "LayoutView",
"align_content": null,
"align_items": null,
"align_self": null,
"border": null,
"bottom": null,
"display": null,
"flex": null,
"flex_flow": null,
"grid_area": null,
"grid_auto_columns": null,
"grid_auto_flow": null,
"grid_auto_rows": null,
"grid_column": null,
"grid_gap": null,
"grid_row": null,
"grid_template_areas": null,
"grid_template_columns": null,
"grid_template_rows": null,
"height": null,
"justify_content": null,
"justify_items": null,
"left": null,
"margin": null,
"max_height": null,
"max_width": null,
"min_height": null,
"min_width": null,
"object_fit": null,
"object_position": null,
"order": null,
"overflow": null,
"overflow_x": null,
"overflow_y": null,
"padding": null,
"right": null,
"top": null,
"visibility": null,
"width": null
}
},
"f9e1cac85c4e43bfb5e87c2b07d2d082": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "HBoxModel",
"state": {
"_dom_classes": [],
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "HBoxModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/controls",
"_view_module_version": "1.5.0",
"_view_name": "HBoxView",
"box_style": "",
"children": [
"IPY_MODEL_26cb5c9cb78349b2b4e3243752093cc4",
"IPY_MODEL_9ad7254e49c84949a63df3569a9f6a34",
"IPY_MODEL_e9461ce46eb3437e8181e7d87031e048"
],
"layout": "IPY_MODEL_f4cde1cee7034425a60ecad0b5c07dda"
}
},
"fad80247656042788748ea5c5c9f64df": {
"model_module": "@jupyter-widgets/base",
"model_module_version": "1.2.0",
"model_name": "LayoutModel",
"state": {
"_model_module": "@jupyter-widgets/base",
"_model_module_version": "1.2.0",
"_model_name": "LayoutModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "LayoutView",
"align_content": null,
"align_items": null,
"align_self": null,
"border": null,
"bottom": null,
"display": null,
"flex": null,
"flex_flow": null,
"grid_area": null,
"grid_auto_columns": null,
"grid_auto_flow": null,
"grid_auto_rows": null,
"grid_column": null,
"grid_gap": null,
"grid_row": null,
"grid_template_areas": null,
"grid_template_columns": null,
"grid_template_rows": null,
"height": null,
"justify_content": null,
"justify_items": null,
"left": null,
"margin": null,
"max_height": null,
"max_width": null,
"min_height": null,
"min_width": null,
"object_fit": null,
"object_position": null,
"order": null,
"overflow": null,
"overflow_x": null,
"overflow_y": null,
"padding": null,
"right": null,
"top": null,
"visibility": null,
"width": null
}
},
"fd706226b91847a39fc3dde16df4ce9d": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "FloatProgressModel",
"state": {
"_dom_classes": [],
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "FloatProgressModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/controls",
"_view_module_version": "1.5.0",
"_view_name": "ProgressView",
"bar_style": "success",
"description": "",
"description_tooltip": null,
"layout": "IPY_MODEL_677de59ed6a941eb980abac52eae5a69",
"max": 1961548,
"min": 0,
"orientation": "horizontal",
"style": "IPY_MODEL_cec0767678744a81a457f9bfa2287e92",
"value": 1961548
}
},
"fde39522ee7e4cd8bf6c5c8e6d07d1c3": {
"model_module": "@jupyter-widgets/controls",
"model_module_version": "1.5.0",
"model_name": "HBoxModel",
"state": {
"_dom_classes": [],
"_model_module": "@jupyter-widgets/controls",
"_model_module_version": "1.5.0",
"_model_name": "HBoxModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/controls",
"_view_module_version": "1.5.0",
"_view_name": "HBoxView",
"box_style": "",
"children": [
"IPY_MODEL_e82aa85c090e40b199df04e9761c0867",
"IPY_MODEL_6869bd240f6a4c27b19fa101cc665001",
"IPY_MODEL_3cc5e854f9a2462fb4eac1b7bbc26ebb"
],
"layout": "IPY_MODEL_c45929291edb45db829d6bf4caeb3cc7"
}
},
"fe84cb01a2fc4803b6959f18b194c476": {
"model_module": "@jupyter-widgets/base",
"model_module_version": "1.2.0",
"model_name": "LayoutModel",
"state": {
"_model_module": "@jupyter-widgets/base",
"_model_module_version": "1.2.0",
"_model_name": "LayoutModel",
"_view_count": null,
"_view_module": "@jupyter-widgets/base",
"_view_module_version": "1.2.0",
"_view_name": "LayoutView",
"align_content": null,
"align_items": null,
"align_self": null,
"border": null,
"bottom": null,
"display": null,
"flex": null,
"flex_flow": null,
"grid_area": null,
"grid_auto_columns": null,
"grid_auto_flow": null,
"grid_auto_rows": null,
"grid_column": null,
"grid_gap": null,
"grid_row": null,
"grid_template_areas": null,
"grid_template_columns": null,
"grid_template_rows": null,
"height": null,
"justify_content": null,
"justify_items": null,
"left": null,
"margin": null,
"max_height": null,
"max_width": null,
"min_height": null,
"min_width": null,
"object_fit": null,
"object_position": null,
"order": null,
"overflow": null,
"overflow_x": null,
"overflow_y": null,
"padding": null,
"right": null,
"top": null,
"visibility": null,
"width": null
}
}
}
}
},
"nbformat": 4,
"nbformat_minor": 0
}