Vigogne-7B-Instruct: A French Instruction-following LLaMA Model
Vigogne-7B-Instruct is a 7 billion parameter LLaMA model developed by bofenghuang, specifically fine-tuned to follow instructions in French. This model is built upon the LLaMA architecture and has undergone several iterations of improvement, primarily focusing on expanding and refining its French instruction-following dataset.
Key Capabilities
- French Instruction Following: Optimized to understand and generate responses based on instructions provided in French.
- LLaMA-7B Base: Leverages the robust LLaMA-7B architecture for its foundational language understanding.
- Iterative Dataset Expansion: Training dataset has been progressively expanded from an initial translated Stanford Alpaca dataset to 262k examples, enhancing performance and instruction adherence.
- Research-Oriented: Intended and licensed for research use only, aligning with the Stanford Alpaca project's licensing.
When to Use This Model
Vigogne-7B-Instruct is particularly well-suited for:
- French NLP Research: Ideal for academic and research projects requiring a capable instruction-following model in French.
- Exploring Multilingual Fine-tuning: Useful for researchers studying the effects of fine-tuning large language models for specific non-English languages.
- Developing French-centric Applications: Can serve as a base for experimental applications that require understanding and generating French text based on user instructions.
Limitations
As an ongoing development, Vigogne-7B-Instruct may still produce harmful, biased, or incorrect content. Its use is restricted to research purposes due to its CC BY NC 4.0 license.