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---
license: apache-2.0
---
# Auto-RAG: Autonomous Retrieval-Augmented Generation for Large Language models
> [Tian Yu](https://tianyu0313.github.io/), [Shaolei Zhang](https://zhangshaolei1998.github.io/), and [Yang Feng](https://people.ucas.edu.cn/~yangfeng?language=en)*
## Model Details
<!-- Provide a longer summary of what this model is. -->
- **Discription:** This is Auto-RAG model trained with synthesized iterative retrieval instruction data. Details can be found in our paper.
- **Developed by:** ICTNLP Group. Authors: Tian Yu, Shaolei Zhang and Yang Feng.
- **Github Repository:** https://github.com/ictnlp/Auto-RAG
- **Paper Link:** https://arxiv.org/abs/2411.19443
- **Finetuned from model:** Meta-Llama3-8B-Instruct
## Uses
<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
You can directly deploy the model using vllm, such as:
```
CUDA_VISIBLE_DEVICES=6,7 python -m vllm.entrypoints.openai.api_server \
--model PATH_TO_MODEL\
--gpu-memory-utilization 0.9 \
-tp 2 \
--max-model-len 8192\
--port 8000\
--host 0.0.0.0
```
## Citation
```
@article{yu2024autorag,
title={Auto-RAG: Autonomous Retrieval-Augmented Generation for Large Language Models},
author={Tian Yu and Shaolei Zhang and Yang Feng},
year={2024},
eprint={2411.19443},
archivePrefix={arXiv},
primaryClass={cs.CL},
url={https://arxiv.org/abs/2411.19443},
}
```
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