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v1.0.7 fix Readme
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README.md

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<a href="https://github.com/MPX0222/SQL-R1/stargazers"><img src="https://img.shields.io/github/stars/MPX0222/SQL-R1?style=flat-square&color=946CE6"/></a>
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</div>
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<div align="center">
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<p>
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<a href="https://github.com/MPX0222">Peixian Ma</a><sup>1,2</sup>&nbsp;&nbsp;
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<a href="https://idea-finai.github.io/SQL-R1/">Xialie Zhuang</a><sup>1,3</sup>&nbsp;&nbsp;
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<a href="https://idea-finai.github.io/SQL-R1/">Chengjin Xu</a><sup>1,4</sup>&nbsp;&nbsp;
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<a href="https://idea-finai.github.io/SQL-R1/">Xuhui Jiang</a><sup>1,4</sup>&nbsp;&nbsp;
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<a href="https://idea-finai.github.io/SQL-R1/">Ran Chen</a><sup>1</sup>&nbsp;&nbsp;
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<a href="https://idea-finai.github.io/SQL-R1/">Jian Guo</a><sup>1</sup>
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</p>
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<p>
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<sup>1</sup>IDEA Research, International Digital Economy Academy
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<sup>2</sup>The Hong Kong University of Science and Technology (Guangzhou)
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<sup>3</sup>University of Chinese Academy of Science
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<sup>4</sup>DataArc Tech Ltd.
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</p>
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</div>
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> 🚧 **Note:** This repository is under active development. We will be continuously updating with model weights, training code, and more resources in the coming weeks. Stay tuned! ✨
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1. Run training:
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```bash
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sh sh/train_sqlr1.sh
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sh sh/train.sh
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```
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2. Run inference:
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## Thanks for
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We thank [OmniSQL](https://github.com/GIST-IRR/OmniSQL) and follow their evaluation code and database information retrieval code. We have adapted and modified their evaluation scripts for our project.
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We thank [OmniSQL](https://github.com/RUCKBReasoning/OmniSQL) and follow their evaluation code and database information retrieval code. We have adapted and modified their evaluation scripts for our project.

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