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| inference: false | |
| license: llama2 | |
| # Vicuna Model Card | |
| ## Model Details | |
| Vicuna is a chat assistant trained by fine-tuning Llama 2 on user-shared conversations collected from ShareGPT. | |
| - **Developed by:** [LMSYS](https://lmsys.org/) | |
| - **Model type:** An auto-regressive language model based on the transformer architecture | |
| - **License:** Llama 2 Community License Agreement | |
| - **Finetuned from model:** [Llama 2](https://arxiv.org/abs/2307.09288) | |
| ### Model Sources | |
| - **Repository:** https://github.com/lm-sys/FastChat | |
| - **Blog:** https://lmsys.org/blog/2023-03-30-vicuna/ | |
| - **Paper:** https://arxiv.org/abs/2306.05685 | |
| - **Demo:** https://chat.lmsys.org/ | |
| ## Uses | |
| The primary use of Vicuna is research on large language models and chatbots. | |
| The primary intended users of the model are researchers and hobbyists in natural language processing, machine learning, and artificial intelligence. | |
| ## How to Get Started with the Model | |
| - Command line interface: https://github.com/lm-sys/FastChat#vicuna-weights | |
| - APIs (OpenAI API, Huggingface API): https://github.com/lm-sys/FastChat/tree/main#api | |
| ## Training Details | |
| Vicuna v1.5 is fine-tuned from Llama 2 with supervised instruction fine-tuning. | |
| The training data is around 125K conversations collected from ShareGPT.com. | |
| See more details in the "Training Details of Vicuna Models" section in the appendix of this [paper](https://arxiv.org/pdf/2306.05685.pdf). | |
| ## Evaluation | |
|  | |
| Vicuna is evaluated with standard benchmarks, human preference, and LLM-as-a-judge. See more details in this [paper](https://arxiv.org/pdf/2306.05685.pdf) and [leaderboard](https://huggingface.co/spaces/lmsys/chatbot-arena-leaderboard). | |
| ## Difference between different versions of Vicuna | |
| See [vicuna_weights_version.md](https://github.com/lm-sys/FastChat/blob/main/docs/vicuna_weights_version.md) |