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--- |
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license: cc-by-nc-4.0 |
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base_model: |
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- Qwen/Qwen2.5-32B-Instruct |
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--- |
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`SweRankLLM-Large` is a 32B LLM based on `Qwen2.5-32B-Instruct` finetuned for listwise code-reranking. When combined with performant code retrievers like `SweRankEmbed`, it significantly enhances the quality of results for software issue localization. |
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The model has been trained on large-scale issue localization data collected from public python github repositories. Check out our [blog post](https://gangiswag.github.io/SweRank/) and [paper](https://arxiv.org/abs/2505.07849) for more details! |
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We release the scripts to evaluate our model's performance [here](https://github.com/gangiswag/SweRank?tab=readme-ov-file#swerankllm-evaluation-reranking). |
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## Citation |
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If you find this model work useful in your research, please consider citing our paper: |
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``` |
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@article{reddy2025swerank, |
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title={SweRank: Software Issue Localization with Code Ranking}, |
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author={Reddy, Revanth Gangi and Suresh, Tarun and Doo, JaeHyeok and Liu, Ye and Nguyen, Xuan Phi and Zhou, Yingbo and Yavuz, Semih and Xiong, Caiming and Ji, Heng and Joty, Shafiq}, |
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journal={arXiv preprint arXiv:2505.07849}, |
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year={2025} |
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} |
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``` |
