--- inference: false --- # longchat-13b-16k Model Card ## Usage 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-13b-16k --task topics (FastChat) python3 -m fastchat.serve.cli --model-path lmsys/longchat-13b-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-13b-16k is an open-source chatbot trained by fine-tuning llama-13b on user-shared conversations collected from ShareGPT, using the condensing rotary embedding technique reported in the [blog](https://lmsys.org/blog/2023-06-29-longchat). **Model date:** longchat-13b-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-13b-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 18K conversations collected from ShareGPT.com. ## Evaluation dataset A preliminary evaluation of the model quality is conducted by our released [LongEval](https://github.com/DachengLi1/LongChat).