| | --- |
| | license: apache-2.0 |
| | library_name: transformers |
| | --- |
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| | # Auto-RAG: Autonomous Retrieval-Augmented Generation for Large Language models |
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| | > [Tian Yu](https://tianyu0313.github.io/), [Shaolei Zhang](https://zhangshaolei1998.github.io/), and [Yang Feng](https://people.ucas.edu.cn/~yangfeng?language=en)* |
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| | ## Model Details |
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| | <!-- Provide a longer summary of what this model is. --> |
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| | - **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 |
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| | ## Uses |
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| | <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. --> |
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| | 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}, |
| | } |
| | ``` |