inference: false
pipeline_tag: conversational
NOTE: New version available
Please check out a newer version of the weights here.
If you still want to use this old version, please see the compatibility and difference between different versions here.
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 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://lmsys.org/blog/2023-03-30-vicuna/
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://lmsys.org/blog/2023-03-30-vicuna/ for more details.