Note: This is a preview version. A slightly better checkpoint will be uploaded soon.

Vicuna Model Card

Model Details

Vicuna is a chat assistant trained by fine-tuning Llama 2 on user-shared conversations collected from ShareGPT.

Developed by: LMSYS
Model type: An auto-regressive language model based on the transformer architecture
License: Llama 2 Community License Agreement
Finetuned from model: Llama 2

Model Sources

Repository: https://github.com/lm-sys/FastChat
Blog: https://lmsys.org/blog/2023-03-30-vicuna/
Paper: https://arxiv.org/abs/2306.05685
Demo: https://chat.lmsys.org/

Uses

The primary use of Vicuna is research on large language models and chatbots. The primary intended users of the model are researchers and hobbyists in natural language processing, machine learning, and artificial intelligence.

How to Get Started with the Model

Command line interface: https://github.com/lm-sys/FastChat#vicuna-weights
APIs (OpenAI API, Huggingface API): https://github.com/lm-sys/FastChat/tree/main#api

Training Details

Vicuna v1.5 (16k) is fine-tuned from Llama 2 with supervised instruction fine-tuning and linear RoPE scaling. The training data is around 125K conversations collected from ShareGPT.com. These conversations are packed into sequences that contain 16K tokens each. See more details in the "Training Details of Vicuna Models" section in the appendix of this paper.

Evaluation

Vicuna is evaluated with standard benchmarks, human preference, and LLM-as-a-judge. See more details in this paper and leaderboard.

Difference between different versions of Vicuna

See vicuna_weights_version.md