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Browse files- README.md +52 -0
- config.json +27 -0
- generation_config.json +7 -0
- model.safetensors +3 -0
- special_tokens_map.json +30 -0
- tokenizer.json +0 -0
- tokenizer_config.json +42 -0
README.md
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---
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license: apache-2.0
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---
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---
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license: apache-2.0
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tags:
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- TinyLlama
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- QLoRA
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- Politics
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- EU
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- News
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- sft
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base_model: TinyLlama/TinyLlama-1.1B-Chat-v1.0
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---
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# TinyPoliticaLlama-1.1B
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TinyPoliticaLlama-1.1B is a SFT fine-tune of [TinyLlama/TinyLlama-1.1B-Chat-v1.0](https://huggingface.co/TinyLlama/TinyLlama-1.1B-Chat-v1.0) and a sister model of [h4rz3rk4s3/TinyParlaMintLlama-1.1B](https://huggingface.co/h4rz3rk4s3/TinyParlaMintLlama-1.1B) and [h4rz3rk4s3/TinyNewsLlama-1.1B](https://huggingface.co/h4rz3rk4s3/TinyNewsLlama-1.1B).
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This model was fine-tuned for ~24h on one A100 40GB on ~225M tokens on the training corpora of both her sister models.
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The goal of this project is to study the potential for improving the domain-specific (in this case political) knowledge of small (<3B) LLMs by concentrating the training datasets TF-IDF in respect to the underlying Topics found in the origianl Dataset.
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The used training data contains speeches from the **Austrian**, **Danish**, **French**, **British**, **Hungarian**, **Dutch**, **Norwegian**, **Polish**, **Swedish** and **Turkish** Parliament, as well as political news articles from **The New York Times**, **USA Today** and **The Washington Times**.
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## 💻 Usage
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```python
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!pip install -qU transformers accelerate
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from transformers import AutoTokenizer, AutoModelForCausalLM
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from accelerate import Accelerator
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import transformers
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import torch
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model = "h4rz3rk4s3/TinyPoliticaLlama-1.1B"
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messages = [
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{
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"role": "system",
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"content": "You are an experienced journalist in the political domain and an expert of European politics.",
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},
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{"role": "user", "content": "Write a short article explaining how the French yellow vest protests started, how they developed over time and how the French Government reacted to the protests."},
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]
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tokenizer = AutoTokenizer.from_pretrained(model)
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prompt = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
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model = AutoModelForCausalLM.from_pretrained(
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model, trust_remote_code=True, device_map={"": Accelerator().process_index}
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)
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pipeline = transformers.pipeline(
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"text-generation",
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tokenizer=tokenizer,
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model=model,
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torch_dtype=torch.float16,
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device_map={"": Accelerator().process_index},
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)
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outputs = pipeline(prompt, max_new_tokens=256, do_sample=True, temperature=0.7, top_k=50, top_p=0.95)
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print(outputs[0]["generated_text"])
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```
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config.json
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{
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"_name_or_path": "/content/drive/MyDrive/Masterarbeit/Tiny-Llama",
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"architectures": [
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"LlamaForCausalLM"
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],
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"attention_bias": false,
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"attention_dropout": 0.0,
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"bos_token_id": 1,
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"eos_token_id": 2,
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"hidden_act": "silu",
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"hidden_size": 2048,
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"initializer_range": 0.02,
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"intermediate_size": 5632,
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"max_position_embeddings": 2048,
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"model_type": "llama",
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"num_attention_heads": 32,
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"num_hidden_layers": 22,
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"num_key_value_heads": 4,
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"rms_norm_eps": 1e-05,
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"rope_scaling": null,
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"rope_theta": 10000.0,
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"tie_word_embeddings": false,
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"torch_dtype": "bfloat16",
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"transformers_version": "4.38.0",
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"use_cache": true,
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"vocab_size": 32000
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}
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generation_config.json
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{
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"bos_token_id": 1,
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"eos_token_id": 2,
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"max_length": 2048,
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"pad_token_id": 0,
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"transformers_version": "4.38.0"
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}
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model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:df0a410e00bb3e3417b21d8550061c5e5fef16975b82ae55bda24df5cefdc4a3
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size 2200119864
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special_tokens_map.json
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{
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"bos_token": {
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"content": "<s>",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": false
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},
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"eos_token": {
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"content": "</s>",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": false
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},
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"pad_token": {
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"content": "</s>",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": false
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},
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"unk_token": {
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"content": "<unk>",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": false
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}
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}
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tokenizer.json
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tokenizer_config.json
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{
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"add_bos_token": true,
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"add_eos_token": false,
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"added_tokens_decoder": {
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"0": {
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"content": "<unk>",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": false,
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"special": true
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},
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"1": {
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"content": "<s>",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": false,
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"special": true
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},
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"2": {
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"content": "</s>",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": false,
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"special": true
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}
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},
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"bos_token": "<s>",
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"chat_template": "{% for message in messages %}\n{% if message['role'] == 'user' %}\n{{ '<|user|>\n' + message['content'] + eos_token }}\n{% elif message['role'] == 'system' %}\n{{ '<|system|>\n' + message['content'] + eos_token }}\n{% elif message['role'] == 'assistant' %}\n{{ '<|assistant|>\n' + message['content'] + eos_token }}\n{% endif %}\n{% if loop.last and add_generation_prompt %}\n{{ '<|assistant|>' }}\n{% endif %}\n{% endfor %}",
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"clean_up_tokenization_spaces": false,
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"eos_token": "</s>",
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"legacy": false,
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"model_max_length": 2048,
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"pad_token": "</s>",
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"padding_side": "right",
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"sp_model_kwargs": {},
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"tokenizer_class": "LlamaTokenizer",
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"unk_token": "<unk>",
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"use_default_system_prompt": false
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}
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