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license: other |
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# Vicuna 7B 1.1 HF |
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This is an HF version of the [Vicuna 7B 1.1 model](https://huggingface.co/lmsys/vicuna-7b-delta-v1.1). |
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It was created by merging the deltas provided in the above repo with the original Llama 7B model, [using the code provided on their Github page](https://github.com/lm-sys/FastChat#vicuna-weights). |
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## My Vicuna 1.1 model repositories |
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I have the following Vicuna 1.1 repositories available: |
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**13B models:** |
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* [Unquantized 13B 1.1 model for GPU - HF format](https://huggingface.co/TheBloke/vicuna-13B-1.1-HF) |
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* [GPTQ quantized 4bit 13B 1.1 for GPU - `safetensors` and `pt` formats](https://huggingface.co/TheBloke/vicuna-13B-1.1-GPTQ-4bit-128g) |
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* [GPTQ quantized 4bit 13B 1.1 for CPU - GGML format for `llama.cpp`](https://huggingface.co/TheBloke/vicuna-13B-1.1-GPTQ-4bit-128g-GGML) |
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**7B models:** |
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* [Unquantized 7B 1.1 model for GPU - HF format](https://huggingface.co/TheBloke/vicuna-7B-1.1-HF) |
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* [GPTQ quantized 4bit 7B 1.1 for GPU - `safetensors` and `pt` formats](https://huggingface.co/TheBloke/vicuna-7B-1.1-GPTQ-4bit-128g) |
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* [GPTQ quantized 4bit 7B 1.1 for CPU - GGML format for `llama.cpp`](https://huggingface.co/TheBloke/vicuna-7B-1.1-GPTQ-4bit-128g-GGML) |
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# 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. |
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## Major updates of weights v1.1 |
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- Refactor the tokenization and separator. In Vicuna v1.1, the separator has been changed from `"###"` to the EOS token `"</s>"`. This change makes it easier to determine the generation stop criteria and enables better compatibility with other libraries. |
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- Fix the supervised fine-tuning loss computation for better model quality. |
