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--- |
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library_name: transformers |
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license: apache-2.0 |
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language: |
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- fr |
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- en |
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datasets: |
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- jpacifico/French-Alpaca-dataset-Instruct-110K |
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tags: |
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- llama3 |
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- french |
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- llama-3-8B |
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--- |
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## Model Card for Model ID |
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French-Alpaca based on Llama3-8B-Instruct |
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![image/jpeg](https://github.com/jpacifico/French-Alpaca/blob/main/Assets/French-Alpaca_500px.png?raw=true) |
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### Model Description |
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fine-tuned from the original French-Alpaca-dataset entirely generated with OpenAI GPT-3.5-turbo. |
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French-Alpaca is a general model and can itself be finetuned to be specialized for specific use cases. |
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The fine-tuning method is inspired from https://crfm.stanford.edu/2023/03/13/alpaca.html |
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Quantized Q4_K_M GGUF 4bits version available : jpacifico/french-alpaca-llama3-4bits-GGUF |
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### Usage |
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```python |
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model_id = "jpacifico/French-Alpaca-Llama3-8B-Instruct-v1.0" |
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model = AutoModelForCausalLM.from_pretrained(model_id, quantization_config=bnb_config, device_map={"":0}) |
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tokenizer = AutoTokenizer.from_pretrained(model_id, add_eos_token=True, padding_side='left') |
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streamer = TextStreamer(tokenizer, timeout=10.0, skip_prompt=True, skip_special_tokens=True) |
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def stream_frenchalpaca(user_prompt): |
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runtimeFlag = "cuda:0" |
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system_prompt = 'Tu trouveras ci-dessous une instruction qui décrit une tâche. Rédige une réponse qui complète de manière appropriée la demande.\n\n' |
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B_INST, E_INST = "### Instruction:\n", "### Response:\n" |
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prompt = f"{system_prompt}{B_INST}{user_prompt.strip()}\n\n{E_INST}" |
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inputs = tokenizer([prompt], return_tensors="pt").to(runtimeFlag) |
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streamer = TextStreamer(tokenizer, skip_prompt=True, skip_special_tokens=True) |
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_ = model.generate(**inputs, streamer=streamer, max_new_tokens=500) |
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stream_frenchalpaca("your prompt here") |
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``` |
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Colab notebook available on my Github : |
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https://github.com/jpacifico/French-Alpaca/blob/main/French_Alpaca_Llama3_inference_test_colab.ipynb |
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### Limitations |
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The French-Alpaca model is a quick demonstration that a base 8B model can be easily fine-tuned to specialize in a particular language. |
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It does not have any moderation mechanisms. |
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- **Developed by:** Jonathan Pacifico, 2024 |
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- **Model type:** LLM |
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- **Language(s) (NLP):** French |
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- **License:** MIT |