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Model: bofenghuang/vigogne-7b-chat Source: Original Platform
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README.md
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README.md
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---
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license: openrail
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language:
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- fr
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pipeline_tag: text-generation
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library_name: transformers
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tags:
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- llama
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- LLM
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inference: false
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---
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<p align="center" width="100%">
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<img src="https://huggingface.co/bofenghuang/vigogne-7b-chat/resolve/main/vigogne_logo.png" alt="Vigogne" style="width: 40%; min-width: 300px; display: block; margin: auto;">
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</p>
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# Vigogne-7B-Chat: A French Chat LLaMA Model
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Vigogne-7B-Chat is a LLaMA-7B model fine-tuned to conduct multi-turn dialogues in 🇫🇷 French between human user and AI assistant.
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For more information, please visit the Github repo: https://github.com/bofenghuang/vigogne
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**Usage and License Notices**: Same as [Stanford Alpaca](https://github.com/tatsu-lab/stanford_alpaca), Vigogne is intended and licensed for research use only. The dataset is CC BY NC 4.0 (allowing only non-commercial use) and models trained using the dataset should not be used outside of research purposes.
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## Usage
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```python
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import torch
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from transformers import AutoModelForCausalLM, AutoTokenizer, GenerationConfig
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from vigogne.preprocess import generate_inference_chat_prompt
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model_name_or_path = "bofenghuang/vigogne-7b-chat"
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tokenizer = AutoTokenizer.from_pretrained(model_name_or_path, padding_side="right", use_fast=False)
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model = AutoModelForCausalLM.from_pretrained(model_name_or_path, torch_dtype=torch.float16, device_map="auto")
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user_query = "Expliquez la différence entre DoS et phishing."
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prompt = generate_inference_chat_prompt([[user_query, ""]], tokenizer=tokenizer)
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input_ids = tokenizer(prompt, return_tensors="pt")["input_ids"].to(model.device)
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input_length = input_ids.shape[1]
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generated_outputs = model.generate(
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input_ids=input_ids,
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generation_config=GenerationConfig(
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temperature=0.1,
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do_sample=True,
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repetition_penalty=1.0,
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max_new_tokens=512,
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),
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return_dict_in_generate=True,
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)
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generated_tokens = generated_outputs.sequences[0, input_length:]
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generated_text = tokenizer.decode(generated_tokens, skip_special_tokens=True)
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print(generated_text)
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```
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You can infer this model by using the following Google Colab Notebook.
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<a href="https://colab.research.google.com/github/bofenghuang/vigogne/blob/main/notebooks/infer_chat.ipynb" target="_blank"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"/></a>
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## Limitations
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Vigogne is still under development, and there are many limitations that have to be addressed. Please note that it is possible that the model generates harmful or biased content, incorrect information or generally unhelpful answers.
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config.json
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{
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"_name_or_path": "huggyllama/llama-7b",
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"architectures": [
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"LlamaForCausalLM"
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],
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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": 4096,
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"initializer_range": 0.02,
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"model_type": "llama",
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||||
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|
||||
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|
||||
23
special_tokens_map.json
Normal file
23
special_tokens_map.json
Normal file
@@ -0,0 +1,23 @@
|
||||
{
|
||||
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|
||||
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|
||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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|
||||
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||||
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||||
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||||
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||||
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||||
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|
||||
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|
||||
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|
||||
}
|
||||
BIN
tokenizer.model
(Stored with Git LFS)
Normal file
BIN
tokenizer.model
(Stored with Git LFS)
Normal file
Binary file not shown.
34
tokenizer_config.json
Normal file
34
tokenizer_config.json
Normal file
@@ -0,0 +1,34 @@
|
||||
{
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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||||
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||||
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||||
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|
||||
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|
||||
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|
||||
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||||
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||||
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||||
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||||
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|
||||
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|
||||
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||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
"unk_token": {
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
}
|
||||
}
|
||||
BIN
vigogne_logo.png
Normal file
BIN
vigogne_logo.png
Normal file
Binary file not shown.
|
After Width: | Height: | Size: 311 KiB |
Reference in New Issue
Block a user