vicuna-13b-delta-v0 / README.md
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metadata
license: apache-2.0
inference: false

NOTE: New version available
Please check out a newer version of the weights at https://huggingface.co/lmsys/vicuna-13b-delta-v1.1
If you still want to use this old version, please see the compatibility and difference between different versions at https://github.com/lm-sys/FastChat/blob/main/docs/vicuna_weights_version.md

NOTE: This "delta model" cannot be used directly.
Users have to apply it on top of the original LLaMA weights to get actual Vicuna weights.
See https://github.com/lm-sys/FastChat#vicuna-weights for instructions.



Vicuna Model Card

Model details

Model type: Vicuna is an open-source chatbot trained by fine-tuning LLaMA on user-shared conversations collected from ShareGPT. It is an auto-regressive language model, based on the transformer architecture.

Model date: Vicuna was trained between March 2023 and April 2023.

Organizations developing the model: The Vicuna team with members from UC Berkeley, CMU, Stanford, and UC San Diego.

Paper or resources for more information: https://vicuna.lmsys.org/

License: Apache License 2.0

Where to send questions or comments about the model: https://github.com/lm-sys/FastChat/issues

Intended use

Primary intended uses: The primary use of Vicuna is research on large language models and chatbots.

Primary intended users: The primary intended users of the model are researchers and hobbyists in natural language processing, machine learning, and artificial intelligence.

Training dataset

70K conversations collected from ShareGPT.com.

Evaluation dataset

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.