bofenghuang/vigostral-7b-chat

TEXT GENERATIONConcurrency Cost:1Model Size:7BQuant:FP8Ctx Length:8kPublished:Sep 29, 2023License:apache-2.0Architecture:Transformer0.0K Open Weights Cold

Vigostral-7B-Chat is a 7 billion parameter French chat LLM developed by bofenghuang, fine-tuned on Mistral-7B-v0.1. This model is specifically designed for conversational AI in French, leveraging a context length of 8192 tokens. It excels at generating human-like responses in French chat scenarios, making it suitable for applications requiring French language interaction.

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Vigostral-7B-Chat: A French Conversational LLM

Vigostral-7B-Chat is a 7 billion parameter large language model, part of the Vigogne LLMs family, developed by bofenghuang. It is fine-tuned from the Mistral-7B-v0.1 base model, specifically optimized for French language chat applications. The model utilizes a prompt template adapted from Llama-2's chat format, ensuring consistent and effective conversational interactions.

Key Capabilities & Features

  • French Language Optimization: Primarily designed and fine-tuned for generating responses in French.
  • Conversational AI: Excels in chat-based interactions, following a structured prompt template.
  • Mistral-7B-v0.1 Base: Built upon the robust Mistral-7B-v0.1 architecture.
  • Quantized Versions Available: Readily available in AWQ, GPTQ, and GGUF formats via TheBloke for efficient inference on various hardware.
  • Flexible Inference: Supports inference using Hugging Face Transformers and vLLM, including an OpenAI-compatible API server.

Usage Considerations

  • License: A significant portion of its training data is distilled from GPT-3.5-Turbo and GPT-4; users should exercise caution to comply with OpenAI's terms of use.
  • Limitations: Still under development, it may occasionally generate harmful, biased, incorrect, or unhelpful content.

Popular Sampler Settings

Top 3 parameter combinations used by Featherless users for this model. Click a tab to see each config.

temperature
top_p
top_k
frequency_penalty
presence_penalty
repetition_penalty
min_p