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--- |
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base_model: |
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- Qwen/Qwen2.5-Coder-32B-Instruct |
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datasets: |
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- SWE-bench/SWE-smith |
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language: |
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- en |
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library_name: transformers |
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license: apache-2.0 |
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pipeline_tag: text-generation |
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tags: |
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- agent |
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- software engineering |
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--- |
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<div align="center"> |
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<img src="https://swe-agent.com/latest/assets/swe-agent.svg" alt="Logo" width="200"> |
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<h1 align="center">SWE-agent LM</h1> |
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</div> |
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<p align="center"> |
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<a href="https://github.com/SWE-bench/SWE-smith">Code</a> |
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• |
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<a href="https://arxiv.org/abs/2504.21798">Paper</a> |
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• |
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<a href="https://swesmith.com/">Site</a> |
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</p> |
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SWE-agent-LM-32B is a Language Model for Software Engineering trained using the [SWE-smith](https://github.com/SWE-bench/SWE-smith) toolkit. |
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We introduce this model as part of our work: [SWE-smith: Scaling Data for Software Engineering Agents](https://swesmith.com). |
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SWE-agent-LM-32B is 100% open source. |
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Training this model was simple - we fine-tuned Qwen 2.5 Coder Instruct on 5k trajectories generated by SWE-agent + Claude 3.7 Sonnet. |
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The dataset can be found [here](https://huggingface.co/datasets/SWE-bench/SWE-smith-trajs-250429). |
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SWE-agent-LM-32B is compatible with [SWE-agent](https://github.com/SWE-agent/SWE-agent). |
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Running this model locally only takes a few steps! |
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Check [here]() for more instructions on how to do so. |
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If you found this work exciting and want to push SWE-agents further, please feel free to connect with us (the [SWE-bench team](https://swe-bench.github.io/)) more! |
