longchat-7b-16k

longchat-7b-16k Model Card

Please use load_model from FastChat or LongChat repo to load the model (or chatting API from FastChat). There is a monkey patch needed to use the model. Usage referece:

(LongChat) python3 eval.py --model-name-or-path lmsys/longchat-7b-16k --task topics

(FastChat) python3 -m fastchat.serve.cli --model-path lmsys/longchat-7b-16k

Under the hood, the monkey patch is added in:

https://github.com/lm-sys/FastChat/blob/da0641e567cf93756b0978ab5a6b092e96f06240/fastchat/model/model_adapter.py#L429

Model details

Model type: longchat-7b-16k is an open-source chatbot trained by fine-tuning llama-7b on user-shared conversations collected from ShareGPT, using the condensing rotary embedding technique reported in the blog.

Model date: longchat-7b-16k was trained on June 2023.

Organizations developing the model: The LongChat developers: Dacheng Li*, Rulin Shao*, Anze Xie, Ying Sheng, Lianmin Zheng, Ion Stoica, Xuezhe Ma, and Hao Zhang

Paper or resources for more information: https://github.com/DachengLi1/LongChat

Where to send questions or comments about the model: https://github.com/DachengLi1/LongChat

Intended use

Primary intended uses: The primary use of longchat-7b-16k is for research purposes.

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

Training dataset

80K conversations collected from ShareGPT.com.

Evaluation dataset

A preliminary evaluation of the model quality is conducted by our released LongEval.