README.md

---
library_name: peft
pipeline_tag: conversational
base_model: meta-llama/Llama-2-7b-hf
---

<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

Llama-2-7b-qlora-msagent-react is fine-tuned from [Llama-2-7b](https://huggingface.co./meta-llama/Llama-2-7b-hf) 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 meta-llama/Llama-2-7b-hf --adapter xtuner/Llama-2-7b-qlora-msagent-react --lagent
```

#### Fine-tune

Use the following command to quickly reproduce the fine-tuning results.

```shell
NPROC_PER_NODE=8 xtuner train llama2_7b_qlora_msagent_react_e3_gpu8
```