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README.md
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# Vicuna Model Card
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## Model
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Vicuna is an open-source chatbot trained by fine-tuning LLaMA on user-shared conversations collected from ShareGPT.
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It is an auto-regressive language model, based on the transformer architecture.
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The Vicuna team with members from UC Berkeley, CMU, Stanford, and UC San Diego.
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**
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https://lmsys.org/blog/2023-03-30-vicuna/
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https://github.com/lm-sys/FastChat/issues
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## Intended use
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**Primary intended uses:**
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The primary use of Vicuna is research on large language models and chatbots.
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**Primary intended users:**
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The primary intended users of the model are researchers and hobbyists in natural language processing, machine learning, and artificial intelligence.
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##
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##
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See https://lmsys.org/blog/2023-03-30-vicuna/ for more details.
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# Vicuna Model Card
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## Model Details
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Vicuna is a chat assistant trained by fine-tuning LLaMA on user-shared conversations collected from ShareGPT.
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- **Developed by:** [LMSYS](https://lmsys.org/)
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- **Model type:** An auto-regressive language model based on the transformer architecture.
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- **License:** Non-commercial license
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- **Finetuned from model:** [LLaMA](https://arxiv.org/abs/2302.13971).
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### Model Sources
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- **Repository:** https://github.com/lm-sys/FastChat
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- **Blog:** https://lmsys.org/blog/2023-03-30-vicuna/
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- **Paper:** https://arxiv.org/abs/2306.05685
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- **Demo:** https://chat.lmsys.org/
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## Uses
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The primary use of Vicuna is research on large language models and chatbots.
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The primary intended users of the model are researchers and hobbyists in natural language processing, machine learning, and artificial intelligence.
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## How to Get Started with the Model
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Command line interface: https://github.com/lm-sys/FastChat#vicuna-weights.
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APIs (OpenAI API, Huggingface API): https://github.com/lm-sys/FastChat/tree/main#api.
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## Training Details
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Vicuna v0 is fine-tuned from LLaMA with supervised instruction fine-tuning.
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The training data is around 70K conversations collected from ShareGPT.com.
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See more details in the "Training Details of Vicuna Models" section in the appendix of this [paper](https://arxiv.org/pdf/2306.05685.pdf).
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## Evaluation
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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).
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## Difference between different versions of Vicuna
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See [vicuna_weights_version.md](https://github.com/lm-sys/FastChat/blob/main/docs/vicuna_weights_version.md)
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