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---
library_name: peft
datasets:
- timdettmers/openassistant-guanaco
pipeline_tag: conversational
base_model: internlm/internlm2-chat-7b
---
<div align="center">
<img src="https://github.com/InternLM/lmdeploy/assets/36994684/0cf8d00f-e86b-40ba-9b54-dc8f1bc6c8d8" width="600"/>
[](https://github.com/InternLM/xtuner)
</div>
## Model
internlm2-chat-7b-qlora-oasst1 is fine-tuned from [InternLM2-Chat-7B](https://huggingface.co/internlm/internlm2-chat-7b) with [openassistant-guanaco](https://huggingface.co/datasets/timdettmers/openassistant-guanaco) dataset by [XTuner](https://github.com/InternLM/xtuner).
## Quickstart
### Usage with XTuner CLI
#### Installation
```shell
pip install xtuner
```
#### Chat
```shell
xtuner chat internlm/internlm2-chat-7b --adapter xtuner/internlm2-chat-7b-qlora-oasst1 --prompt-template internlm2_chat
```
#### Fine-tune
Use the following command to quickly reproduce the fine-tuning results.
```shell
xtuner train internlm2_chat_7b_qlora_oasst1_e3
```
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