From 677bc3ac240fb4dcd6a259f8af6c24d4200117c3 Mon Sep 17 00:00:00 2001 From: ModelHub XC Date: Tue, 26 May 2026 09:10:16 +0800 Subject: [PATCH] =?UTF-8?q?=E5=88=9D=E5=A7=8B=E5=8C=96=E9=A1=B9=E7=9B=AE?= =?UTF-8?q?=EF=BC=8C=E7=94=B1ModelHub=20XC=E7=A4=BE=E5=8C=BA=E6=8F=90?= =?UTF-8?q?=E4=BE=9B=E6=A8=A1=E5=9E=8B?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit Model: bofenghuang/vigostral-7b-chat Source: Original Platform --- .gitattributes | 35 ++++ README.md | 208 +++++++++++++++++++++ added_tokens.json | 5 + config.json | 25 +++ generation_config.json | 6 + pytorch_model-00001-of-00002.bin | 3 + pytorch_model-00002-of-00002.bin | 3 + pytorch_model.bin.index.json | 298 +++++++++++++++++++++++++++++++ special_tokens_map.json | 5 + tokenizer.model | 3 + tokenizer_config.json | 45 +++++ 11 files changed, 636 insertions(+) create mode 100644 .gitattributes create mode 100644 README.md create mode 100644 added_tokens.json create mode 100644 config.json create mode 100644 generation_config.json create mode 100644 pytorch_model-00001-of-00002.bin create mode 100644 pytorch_model-00002-of-00002.bin create mode 100644 pytorch_model.bin.index.json create mode 100644 special_tokens_map.json create mode 100644 tokenizer.model create mode 100644 tokenizer_config.json diff --git a/.gitattributes b/.gitattributes new file mode 100644 index 0000000..a6344aa --- /dev/null +++ b/.gitattributes @@ -0,0 +1,35 @@ +*.7z filter=lfs diff=lfs merge=lfs -text +*.arrow filter=lfs diff=lfs merge=lfs -text +*.bin filter=lfs diff=lfs merge=lfs -text +*.bz2 filter=lfs diff=lfs merge=lfs -text +*.ckpt filter=lfs diff=lfs merge=lfs -text +*.ftz filter=lfs diff=lfs merge=lfs -text +*.gz filter=lfs diff=lfs merge=lfs -text +*.h5 filter=lfs diff=lfs merge=lfs -text +*.joblib filter=lfs diff=lfs merge=lfs -text +*.lfs.* filter=lfs diff=lfs merge=lfs -text +*.mlmodel filter=lfs diff=lfs merge=lfs -text +*.model filter=lfs diff=lfs merge=lfs -text +*.msgpack filter=lfs diff=lfs merge=lfs -text +*.npy filter=lfs diff=lfs merge=lfs -text +*.npz filter=lfs diff=lfs merge=lfs -text +*.onnx filter=lfs diff=lfs merge=lfs -text +*.ot filter=lfs diff=lfs merge=lfs -text +*.parquet filter=lfs diff=lfs merge=lfs -text +*.pb filter=lfs diff=lfs merge=lfs -text +*.pickle filter=lfs diff=lfs merge=lfs -text +*.pkl filter=lfs diff=lfs merge=lfs -text +*.pt filter=lfs diff=lfs merge=lfs -text +*.pth filter=lfs diff=lfs merge=lfs -text +*.rar filter=lfs diff=lfs merge=lfs -text +*.safetensors filter=lfs diff=lfs merge=lfs -text +saved_model/**/* filter=lfs diff=lfs merge=lfs -text +*.tar.* filter=lfs diff=lfs merge=lfs -text +*.tar filter=lfs diff=lfs merge=lfs -text +*.tflite filter=lfs diff=lfs merge=lfs -text +*.tgz filter=lfs diff=lfs merge=lfs -text +*.wasm filter=lfs diff=lfs merge=lfs -text +*.xz filter=lfs diff=lfs merge=lfs -text +*.zip filter=lfs diff=lfs merge=lfs -text +*.zst filter=lfs diff=lfs merge=lfs -text +*tfevents* filter=lfs diff=lfs merge=lfs -text diff --git a/README.md b/README.md new file mode 100644 index 0000000..5287d8b --- /dev/null +++ b/README.md @@ -0,0 +1,208 @@ +--- +license: apache-2.0 +language: fr +pipeline_tag: text-generation +inference: + parameters: + temperature: 0.7 +tags: +- LLM +- finetuned +--- + +# Vigostral-7B-Chat: A French chat LLM + +***Preview*** of Vigostral-7B-Chat, a new addition to the Vigogne LLMs family, fine-tuned on [Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1). + +For more information, please visit the [Github repository](https://github.com/bofenghuang/vigogne). + +**License**: A significant portion of the training data is distilled from GPT-3.5-Turbo and GPT-4, kindly use it cautiously to avoid any violations of OpenAI's [terms of use](https://openai.com/policies/terms-of-use). + +## Prompt Template + +We used a prompt template adapted from the chat format of Llama-2. + +You can apply this formatting using the [chat template](https://huggingface.co/docs/transformers/main/chat_templating) through the `apply_chat_template()` method. + +```python +from transformers import AutoTokenizer + +tokenizer = AutoTokenizer.from_pretrained("bofenghuang/vigostral-7b-chat") + +conversation = [ + {"role": "user", "content": "Bonjour ! Comment ça va aujourd'hui ?"}, + {"role": "assistant", "content": "Bonjour ! Je suis une IA, donc je n'ai pas de sentiments, mais je suis prêt à vous aider. Comment puis-je vous assister aujourd'hui ?"}, + {"role": "user", "content": "Quelle est la hauteur de la Tour Eiffel ?"}, + {"role": "assistant", "content": "La Tour Eiffel mesure environ 330 mètres de hauteur."}, + {"role": "user", "content": "Comment monter en haut ?"}, +] + +print(tokenizer.apply_chat_template(conversation, tokenize=False, add_generation_prompt=True)) +``` + +You will get + +``` +[INST] <> +Vous êtes Vigogne, un assistant IA créé par Zaion Lab. Vous suivez extrêmement bien les instructions. Aidez autant que vous le pouvez. +<> + +Bonjour ! Comment ça va aujourd'hui ? [/INST] Bonjour ! Je suis une IA, donc je n'ai pas de sentiments, mais je suis prêt à vous aider. Comment puis-je vous assister aujourd'hui ? [INST] Quelle est la hauteur de la Tour Eiffel ? [/INST] La Tour Eiffel mesure environ 330 mètres de hauteur. [INST] Comment monter en haut ? [/INST] +``` + +## Usage + +### Inference using the quantized versions + +The quantized versions of this model are generously provided by [TheBloke](https://huggingface.co/TheBloke)! + +- AWQ for GPU inference: [TheBloke/Vigostral-7B-Chat-AWQ](https://huggingface.co/TheBloke/Vigostral-7B-Chat-AWQ) +- GTPQ for GPU inference: [TheBloke/Vigostral-7B-Chat-GPTQ](https://huggingface.co/TheBloke/Vigostral-7B-Chat-GPTQ) +- GGUF for CPU+GPU inference: [TheBloke/Vigostral-7B-Chat-GGUF](https://huggingface.co/TheBloke/Vigostral-7B-Chat-GGUF) + +These versions facilitate testing and development with various popular frameworks, including [AutoAWQ](https://github.com/casper-hansen/AutoAWQ), [vLLM](https://github.com/vllm-project/vllm), [AutoGPTQ](https://github.com/PanQiWei/AutoGPTQ), [GPTQ-for-LLaMa](https://github.com/qwopqwop200/GPTQ-for-LLaMa), [llama.cpp](https://github.com/ggerganov/llama.cpp), [text-generation-webui](https://github.com/oobabooga/text-generation-webui), and more. + +### Inference using the unquantized model with 🤗 Transformers + +```python +from typing import Dict, List, Optional +import torch +from transformers import AutoModelForCausalLM, AutoTokenizer, GenerationConfig, TextStreamer + +model_name_or_path = "bofenghuang/vigostral-7b-chat" +tokenizer = AutoTokenizer.from_pretrained(model_name_or_path, padding_side="right", use_fast=False) +model = AutoModelForCausalLM.from_pretrained(model_name_or_path, torch_dtype=torch.float16, device_map="auto") + +streamer = TextStreamer(tokenizer, timeout=10.0, skip_prompt=True, skip_special_tokens=True) + + +def chat( + query: str, + history: Optional[List[Dict]] = None, + temperature: float = 0.7, + top_p: float = 1.0, + top_k: float = 0, + repetition_penalty: float = 1.1, + max_new_tokens: int = 1024, + **kwargs, +): + if history is None: + history = [] + + history.append({"role": "user", "content": query}) + + input_ids = tokenizer.apply_chat_template(history, return_tensors="pt").to(model.device) + input_length = input_ids.shape[1] + + generated_outputs = model.generate( + input_ids=input_ids, + generation_config=GenerationConfig( + temperature=temperature, + do_sample=temperature > 0.0, + top_p=top_p, + top_k=top_k, + repetition_penalty=repetition_penalty, + max_new_tokens=max_new_tokens, + pad_token_id=tokenizer.eos_token_id, + **kwargs, + ), + streamer=streamer, + return_dict_in_generate=True, + ) + + generated_tokens = generated_outputs.sequences[0, input_length:] + generated_text = tokenizer.decode(generated_tokens, skip_special_tokens=True) + + history.append({"role": "assistant", "content": generated_text}) + + return generated_text, history + + +# 1st round +response, history = chat("Un escargot parcourt 100 mètres en 5 heures. Quelle est sa vitesse ?", history=None) + +# 2nd round +response, history = chat("Quand il peut dépasser le lapin ?", history=history) + +# 3rd round +response, history = chat("Écris une histoire imaginative qui met en scène une compétition de course entre un escargot et un lapin.", history=history) +``` + +You can also use the Google Colab Notebook provided below. + +Open In Colab + +### Inference using the unquantized model with vLLM + +Set up an OpenAI-compatible server with the following command: + +```bash +# Install vLLM +# This may take 5-10 minutes. +# pip install vllm + +# Start server for Vigostral-Chat models +python -m vllm.entrypoints.openai.api_server --model bofenghuang/vigostral-7b-chat + +# List models +# curl http://localhost:8000/v1/models +``` + +You can also use the docker image provided below. + +```bash +# Launch inference engine +docker run --gpus '"device=0"' \ + -e HF_TOKEN=$HF_TOKEN -p 8000:8000 \ + ghcr.io/bofenghuang/vigogne/vllm:latest \ + --host 0.0.0.0 \ + --model bofenghuang/vigostral-7b-chat + +# Launch inference engine on mutli-GPUs (4 here) +docker run --gpus all \ + -e HF_TOKEN=$HF_TOKEN -p 8000:8000 \ + ghcr.io/bofenghuang/vigogne/vllm:latest \ + --host 0.0.0.0 \ + --tensor-parallel-size 4 \ + --model bofenghuang/vigostral-7b-chat + +# Launch inference engine using the quantized AWQ version +# Note only supports Ampere or newer GPUs +docker run --gpus '"device=0"' \ + -e HF_TOKEN=$HF_TOKEN -p 8000:8000 \ + ghcr.io/bofenghuang/vigogne/vllm:latest \ + --host 0.0.0.0 \ + --quantization awq \ + --model TheBloke/Vigostral-7B-Chat-AWQ +``` + +Afterward, you can query the model using the openai Python package. + +```python +import openai + +# Modify OpenAI's API key and API base to use vLLM's API server. +openai.api_key = "EMPTY" +openai.api_base = "http://localhost:8000/v1" + +# First model +models = openai.Model.list() +model = models["data"][0]["id"] + +query_message = "Parle-moi de toi-même." + +# Chat completion API +chat_completion = openai.ChatCompletion.create( + model=model, + messages=[ + {"role": "user", "content": query_message}, + ], + max_tokens=1024, + temperature=0.7, +) +print("Chat completion results:", chat_completion) +``` + +## Limitations + +Vigogne is still under development, and there are many limitations that have to be addressed. 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"add_eos_token": false, + "added_tokens_decoder": { + "0": { + "content": "", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "1": { + "content": "", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "2": { + "content": "", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + } + }, + "additional_special_tokens": [], + "bos_token": "", + "chat_template": "{{ bos_token }}{% if messages[0]['role'] == 'system' %}{% set loop_messages = messages[1:] %}{% set system_message = messages[0]['content'] %}{% elif true == true and not '<>' in messages[0]['content'] %}{% set loop_messages = messages %}{% set system_message = 'Vous êtes Vigogne, un assistant IA créé par Zaion Lab. Vous suivez extrêmement bien les instructions. Aidez autant que vous le pouvez.' %}{% else %}{% set loop_messages = messages %}{% set system_message = false %}{% endif %}{% for message in loop_messages %}{% if (message['role'] == 'user') != (loop.index0 % 2 == 0) %}{{ raise_exception('Conversation roles must alternate user/assistant/user/assistant/...') }}{% endif %}{% if loop.index0 == 0 and system_message != false %}{% set content = '<>\\n' + system_message + '\\n<>\\n\\n' + message['content'] %}{% else %}{% set content = message['content'] %}{% endif %}{% if message['role'] == 'user' %}{{ '[INST] ' + content.strip() + ' [/INST]' }}{% elif message['role'] == 'system' %}{{ '<>\\n' + content.strip() + '\\n<>\\n\\n' }}{% elif message['role'] == 'assistant' %}{{ ' ' + content.strip() + ' ' + eos_token }}{% endif %}{% endfor %}", + "clean_up_tokenization_spaces": false, + "eos_token": "", + "legacy": true, + "model_max_length": 1000000000000000019884624838656, + "pad_token": null, + "padding_side": "right", + "sp_model_kwargs": {}, + "spaces_between_special_tokens": false, + "tokenizer_class": "LlamaTokenizer", + "tokenizer_file": null, + "unk_token": "", + "use_default_system_prompt": true +}