|
--- |
|
inference: false |
|
license: llama2 |
|
--- |
|
|
|
# Vicuna Model Card |
|
|
|
## Model Details |
|
|
|
Vicuna is a chat assistant trained by fine-tuning LLaMA on user-shared conversations collected from ShareGPT. |
|
|
|
- **Developed by:** [LMSYS](https://lmsys.org/) |
|
- **Model type:** An auto-regressive language model based on the transformer architecture |
|
- **License:** Non-commercial license |
|
- **Finetuned from model:** [LLaMA 2](https://arxiv.org/abs/2307.09288) |
|
|
|
### 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 is fine-tuned from LLaMA with supervised instruction fine-tuning. |
|
The training data is around 125K conversations collected from ShareGPT.com. |
|
See more details in the "Training Details of Vicuna Models" section in the appendix of this [paper](https://arxiv.org/pdf/2306.05685.pdf). |
|
|
|
## Evaluation |
|
|
|
Vicuna is evaluated with standard benchmarks, human preference, and LLM-as-a-judge. See more details in this [paper](https://arxiv.org/pdf/2306.05685.pdf) and [leaderboard](https://huggingface.co/spaces/lmsys/chatbot-arena-leaderboard). |
|
|
|
## Difference between different versions of Vicuna |
|
See [vicuna_weights_version.md](https://github.com/lm-sys/FastChat/blob/main/docs/vicuna_weights_version.md) |
