--- library_name: transformers license: apache-2.0 language: - fr - en datasets: - jpacifico/French-Alpaca-dataset-Instruct-110K tags: - llama3 - french - llama-3-8B --- ## Model Card for Model ID French-Alpaca based on Llama3-8B-Instruct ![image/jpeg](https://github.com/jpacifico/French-Alpaca/blob/main/Assets/French-Alpaca_500px.png?raw=true) ### Model Description fine-tuned from the original French-Alpaca-dataset entirely generated with OpenAI GPT-3.5-turbo. French-Alpaca is a general model and can itself be finetuned to be specialized for specific use cases. The fine-tuning method is inspired from https://crfm.stanford.edu/2023/03/13/alpaca.html Quantized Q4_K_M GGUF 4bits version available : jpacifico/french-alpaca-llama3-8B-Q4-GGUF ### Usage ```python model_id = "jpacifico/French-Alpaca-Llama3-8B-Instruct-v1.0" model = AutoModelForCausalLM.from_pretrained(model_id, quantization_config=bnb_config, device_map={"":0}) tokenizer = AutoTokenizer.from_pretrained(model_id, add_eos_token=True, padding_side='left') streamer = TextStreamer(tokenizer, timeout=10.0, skip_prompt=True, skip_special_tokens=True) def stream_frenchalpaca(user_prompt): runtimeFlag = "cuda:0" system_prompt = 'Tu trouveras ci-dessous une instruction qui décrit une tâche. Rédige une réponse qui complète de manière appropriée la demande.\n\n' B_INST, E_INST = "### Instruction:\n", "### Response:\n" prompt = f"{system_prompt}{B_INST}{user_prompt.strip()}\n\n{E_INST}" inputs = tokenizer([prompt], return_tensors="pt").to(runtimeFlag) streamer = TextStreamer(tokenizer, skip_prompt=True, skip_special_tokens=True) _ = model.generate(**inputs, streamer=streamer, max_new_tokens=500) stream_frenchalpaca("your prompt here") ``` Colab notebook available on my Github : https://github.com/jpacifico/French-Alpaca/blob/main/French_Alpaca_Llama3_inference_test_colab.ipynb ### Limitations The French-Alpaca model is a quick demonstration that a base 8B model can be easily fine-tuned to specialize in a particular language. It does not have any moderation mechanisms. - **Developed by:** Jonathan Pacifico, 2024 - **Model type:** LLM - **Language(s) (NLP):** French - **License:** MIT