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+ ---
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+ license: apache-2.0
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+ inference: false
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+ ---
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+
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+ **NOTE: This "delta model" cannot be used directly.**
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+ Users have to apply it on top of the original LLaMA weights to get actual Vicuna weights.
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+ See https://github.com/lm-sys/FastChat#vicuna-weights for instructions.
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+
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+ <br>
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+ <br>
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+
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+ # Vicuna Model Card
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+
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+ ## Model details
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+
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+ **Model type:**
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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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+
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+ **Model date:**
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+ Vicuna was trained between March 2023 and April 2023.
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+
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+ **Organizations developing the model:**
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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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+ **Paper or resources for more information:**
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+ https://vicuna.lmsys.org/
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+
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+ **License:**
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+ Apache License 2.0
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+
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+ **Where to send questions or comments about the model:**
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+ https://github.com/lm-sys/FastChat/issues
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+
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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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+
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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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+ ## Training dataset
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+ 70K conversations collected from ShareGPT.com.
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+
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+ ## Evaluation dataset
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+ A preliminary evaluation of the model quality is conducted by creating a set of 80 diverse questions and utilizing GPT-4 to judge the model outputs. See https://vicuna.lmsys.org/ for more details.