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license: other |
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# Vicuna 7B without "ethics" filtering |
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This repository contains an alternative version of the [Vicuna 7B model](https://huggingface.co/lmsys/vicuna-7b-delta-v0). |
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This model was natively fine-tuned using ShareGPT data, but without the "ethics" filtering used for the original Vicuna. |
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[A GPTQ quantised 4-bit version is available here](https://huggingface.co/TheBloke/vicuna-AlekseyKorshuk-7B-GPTQ-4bit-128g). |
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# Original Vicuna Model Card |
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## Model details |
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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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**Model date:** |
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Vicuna was trained between March 2023 and April 2023. |
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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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**Paper or resources for more information:** |
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https://vicuna.lmsys.org/ |
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**License:** |
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Apache License 2.0 |
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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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## 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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## Training dataset |
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70K conversations collected from ShareGPT.com. |
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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. |
