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---
library_name: peft
pipeline_tag: conversational
base_model: internlm/internlm-20b
---
<div align="center">
<img src="https://github.com/InternLM/lmdeploy/assets/36994684/0cf8d00f-e86b-40ba-9b54-dc8f1bc6c8d8" width="600"/>
[![Generic badge](https://img.shields.io/badge/GitHub-%20XTuner-black.svg)](https://github.com/InternLM/xtuner)
</div>
## Model
internlm-20b-qlora-msagent-react is fine-tuned from [InternLM-20B](https://huggingface.co/internlm/internlm-20b) with [MSAgent-Bench](https://modelscope.cn/datasets/damo/MSAgent-Bench) dataset by [XTuner](https://github.com/InternLM/xtuner).
## Quickstart
### Usage with XTuner CLI
#### Installation
```shell
pip install xtuner
```
#### Chat
```shell
xtuner chat internlm/internlm-20b --adapter xtuner/internlm-20b-qlora-msagent-react --lagent
```
#### Fine-tune
Use the following command to quickly reproduce the fine-tuning results.
```shell
NPROC_PER_NODE=8 xtuner train internlm_20b_qlora_msagent_react_e3_gpu8
```