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+ ---
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+ License: apache-2.0
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+ Language:
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+ - En
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+ Pipeline_tag: text-generation
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+ Base_model: nvidia/Llama-3.1-Minitron-4 B-Width-Base
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+ Tags:
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+ - Chat
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+ license: agpl-3.0
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+ datasets:
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+ - anthracite-org/kalo-opus-instruct-22k-no-refusal
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+ - PJMixers/lodrick-the-lafted_OpusStories-ShareGPT
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+ - NewEden/Gryphe-3.5-16k-Subset
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+ - Epiculous/Synthstruct-Gens-v1.1-Filtered-n-Cleaned
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+ tags:
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+ - chat
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+ ---
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+
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+ ![image/png](https://huggingface.co/Edens-Gate/Testing123/resolve/main/oie_gM9EsNXjMDsT.jpg?download=true)
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+ A model made to continue off my previous work on [Magnum 4B](https://huggingface.co/anthracite-org/magnum-v2-4b), A small model made for creative writing / General assistant tasks, finetuned ontop of [IntervitensInc/Llama-3.1-Minitron-4B-Width-Base-chatml](https://huggingface.co/IntervitensInc/Llama-3.1-Minitron-4B-Width-Base-chatml), this model is made to be more coherent and generally be better then the 4B at both writing and assistant tasks.
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+
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+ ## Prompting
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+ Model has been Instruct tuned with the ChatML formatting. A typical input would look like this:
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+
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+ ```py
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+ """<|im_start|>system
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+ system prompt<|im_end|>
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+ <|im_start|>user
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+ Hi there!<|im_end|>
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+ <|im_start|>assistant
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+ Nice to meet you!<|im_end|>
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+ <|im_start|>user
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+ Can I ask a question?<|im_end|>
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+ <|im_start|>assistant
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+ """
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+ ```
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+
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+ ## Support
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+
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+ To run inference on this model, you'll need to use Aphrodite, vLLM or EXL 2/tabbyAPI, as llama.cpp hasn't yet merged the required pull request to fix the llama 3.1 rope_freqs issue with custom head dimensions.
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+
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+ However, you can work around this by quantizing the model yourself to create a functional GGUF file. Note that until [this PR](https://github.com/ggerganov/llama.cpp/pull/9141) is merged, the context will be limited to 8 k tokens.
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+
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+ To create a working GGUF file, make the following adjustments:
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+
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+ 1. Remove the `"rope_scaling": {}` entry from `config.json`
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+ 2. Change `"max_position_embeddings"` to `8192` in `config.json`
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+
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+ These modifications should allow you to use the model with llama. Cpp, albeit with the mentioned context limitation.
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+
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+ ## Axolotl config
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+
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+ <details><summary>See axolotl config</summary>
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+
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+ Axolotl version: `0.4.1`
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+ ```yaml
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+ base_model: IntervitensInc/Llama-3.1-Minitron-4B-Width-Base-chatml
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+ model_type: AutoModelForCausalLM
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+ tokenizer_type: AutoTokenizer
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+
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+ load_in_8bit: false
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+ load_in_4bit: false
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+ strict: false
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+
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+ datasets:
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+ - path: NewEden/Gryphe-3.5-16k-Subset
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+ type: sharegpt
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+ conversation: chatml
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+ - path: Epiculous/Synthstruct-Gens-v1.1-Filtered-n-Cleaned
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+ type: sharegpt
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+ conversation: chatml
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+ - path: anthracite-org/kalo-opus-instruct-22k-no-refusal
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+ type: sharegpt
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+ conversation: chatml
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+ - path: PJMixers/lodrick-the-lafted_OpusStories-ShareGPT
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+ type: sharegpt
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+ conversation: chatml
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+
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+ chat_template: chatml
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+
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+ val_set_size: 0.01
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+ output_dir: ./outputs/out
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+
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+ adapter:
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+ lora_r:
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+ lora_alpha:
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+ lora_dropout:
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+ lora_target_linear:
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+
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+ sequence_len: 16384
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+ # sequence_len: 32768
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+ sample_packing: true
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+ eval_sample_packing: false
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+ pad_to_sequence_len: true
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+
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+ plugins:
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+ - axolotl.integrations.liger.LigerPlugin
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+ liger_rope: true
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+ liger_rms_norm: true
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+ liger_swiglu: true
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+ liger_fused_linear_cross_entropy: true
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+
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+ wandb_project:
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+ wandb_entity:
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+ wandb_watch:
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+ wandb_name:
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+ wandb_log_model:
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+
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+ gradient_accumulation_steps: 32
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+ micro_batch_size: 1
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+ num_epochs: 2
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+ optimizer: adamw_bnb_8bit
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+ #optimizer: paged_adamw_8bit
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+ lr_scheduler: cosine
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+ learning_rate: 0.00002
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+ weight_decay: 0.05
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+
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+ train_on_inputs: false
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+ group_by_length: false
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+ bf16: auto
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+ fp16:
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+ tf32: true
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+
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+ gradient_checkpointing: true
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+ early_stopping_patience:
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+ resume_from_checkpoint:
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+ local_rank:
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+ logging_steps: 1
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+ xformers_attention:
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+ flash_attention: true
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+
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+ warmup_ratio: 0.1
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+ evals_per_epoch: 4
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+ eval_table_size:
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+ eval_max_new_tokens: 128
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+ saves_per_epoch: 1
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+
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+ debug:
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+ deepspeed: /workspace/axolotl/deepspeed_configs/zero2.json
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+ #deepspeed:
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+ fsdp:
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+ fsdp_config:
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+
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+ special_tokens:
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+ pad_token: <|finetune_right_pad_id|>
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+
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+ ```
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+
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+ </details><br>
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+
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+ ## Credits
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+
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+ - [anthracite-org/kalo-opus-instruct-22k-no-refusal](https://huggingface.co/datasets/anthracite-org/kalo-opus-instruct-22k-no-refusal)
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+ - [NewEden/Gryphe-3.5-16k-Subset](https://huggingface.co/datasets/NewEden/Gryphe-3.5-16k-Subset)
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+ - [Epiculous/Synthstruct-Gens-v1.1-Filtered-n-Cleaned](https://huggingface.co/datasets/Epiculous/Synthstruct-Gens-v1.1-Filtered-n-Cleaned)
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+ - [lodrick-the-lafted/OpusStories](https://huggingface.co/datasets/lodrick-the-lafted/OpusStories)
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+
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+ I couldn't have made this model without the help of [Kubernetes_bad](https://huggingface.co/kubernetes-bad) and the support of [Lucy Knada](https://huggingface.co/lucyknada)
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+
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+ ## Training
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+ The training was done for 2 epochs. We used 2 x [RTX 6000s](https://store.nvidia.com/en-us/nvidia-rtx/products/nvidia-rtx-6000-ada-generation/) GPUs graciously provided by [Kubernetes_Bad](https://huggingface.co/kubernetes-bad) for the full-parameter fine-tuning of the model.
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+
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+ [<img src="https://raw.githubusercontent.com/OpenAccess-AI-Collective/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/OpenAccess-AI-Collective/axolotl)
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+
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+ ## Safety
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+ ...