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Model: lmsys/longchat-13b-16k
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---
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).

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