CodeIO-PyEdu-Reasoning

# CodeI/O: Condensing Reasoning Patterns via Code Input-Output Prediction <p align="left"> 📑 <a href="https://huggingface.co/papers/2502.07316" target="_blank">Paper</a> &nbsp&nbsp | &nbsp&nbsp 🌐 <a href="https://codei-o.github.io/" target="_blank">Project Page</a> &nbsp&nbsp | &nbsp&nbsp 💾 <a href="https://huggingface.co/collections/hkust-nlp/codei-o-67a978e28fd926b56a4f55a2" target="_blank">Released Resources</a> &nbsp&nbsp | &nbsp&nbsp 📦 <a href="https://github.com/hkust-nlp/CodeIO" target="_blank">Repo</a> This is the resource page of the CodeI/O collection on Huggingface, we highlight your currect position with a blue block. **Dataset** <table> <tr> <th>Dataset</th> <th>Link</th> </tr> <tr> <td>CodeI/O-PythonEdu-Reasoning</td> <td style="background-color: #e6f3ff; text-align: center; vertical-align: middle;"> <a href="https://huggingface.co/datasets/hkust-nlp/CodeIO-PyEdu-Reasoning">🤗</a> </td> </tr> </table> Please also check the raw data after our processing if you are interested: [hkust-nlp/CodeIO-PyEdu-Reasoning-Raw](https://huggingface.co/datasets/hkust-nlp/CodeIO-PyEdu-Reasoning-Raw). **Models** <table> <tr> <th rowspan="2">Base Model / Training</th> <th colspan="2">CodeI/O</th> <th colspan="2">CodeI/O++</th> </tr> <tr> <th>Stage 1</th> <th>Stage 2</th> <th>Stage 1</th> <th>Stage 2</th> </tr> <tr> <td>Qwen 2.5 7B Coder</td> <td style="text-align: center; vertical-align: middle;"><a href="https://huggingface.co/hkust-nlp/qwen2.5-7b-coder_codeio_stage1">🤗</a></td> <td style="text-align: center; vertical-align: middle;"><a href="https://huggingface.co/hkust-nlp/qwen2.5-7b-coder_codeio">🤗</a></td> <td style="text-align: center; vertical-align: middle;"><a href="https://huggingface.co/hkust-nlp/qwen2.5-7b-coder_codeio_pp_stage1">🤗</a></td> <td style="text-align: center; vertical-align: middle;"><a href="https://huggingface.co/hkust-nlp/qwen2.5-7b-coder_codeio_pp">🤗</a></td> </tr> <tr> <td>LLaMA 3.1 8B</td> <td style="text-align: center; vertical-align: middle;"><a href="https://huggingface.co/hkust-nlp/llama3.1-8b_codeio_stage1">🤗</a></td> <td style="text-align: center; vertical-align: middle;"><a href="https://huggingface.co/hkust-nlp/llama3.1-8b_codeio">🤗</a></td> <td style="text-align: center; vertical-align: middle;"><a href="https://huggingface.co/hkust-nlp/llama3.1-8b_codeio_pp_stage1">🤗</a></td> <td style="text-align: center; vertical-align: middle;"><a href="https://huggingface.co/hkust-nlp/llama3.1-8b_codeio_pp">🤗</a></td> </tr> <tr> <td>DeepSeek v2 Lite Coder</td> <td style="text-align: center; vertical-align: middle;"><a href="https://huggingface.co/hkust-nlp/dsv2-lite-coder_codeio_stage1">🤗</a></td> <td style="text-align: center; vertical-align: middle;"><a href="https://huggingface.co/hkust-nlp/dsv2-lite-coder_codeio">🤗</a></td> <td style="text-align: center; vertical-align: middle;"><a href="https://huggingface.co/hkust-nlp/dsv2-lite-coder_codeio_pp_stage1">🤗</a></td> <td style="text-align: center; vertical-align: middle;"><a href="https://huggingface.co/hkust-nlp/dsv2-lite-coder_codeio_pp">🤗</a></td> </tr> </table> ## Citation If you find these resources helpful, please kindly cite as: ``` @article{li2025codeio, title={CodeI/O: Condensing Reasoning Patterns via Code Input-Output Prediction}, author={Li, Junlong and Guo, Daya and Yang, Dejian and Xu, Runxin and Wu, Yu and He, Junxian}, journal={arXiv preprint arXiv:2502.07316}, year={2025} } ```# CodeI/O：基于代码输入-输出预测凝练推理模式 <p align="left"> 📑 <a href="https://huggingface.co/papers/2502.07316" target="_blank">论文</a> &nbsp&nbsp | &nbsp&nbsp 🌐 <a href="https://codei-o.github.io/" target="_blank">项目主页</a> &nbsp&nbsp | &nbsp&nbsp 💾 <a href="https://huggingface.co/collections/hkust-nlp/codei-o-67a978e28fd926b56a4f55a2" target="_blank">已发布资源</a> &nbsp&nbsp | &nbsp&nbsp 📦 <a href="https://github.com/hkust-nlp/CodeIO" target="_blank">代码仓库</a> </p> 本页面为Huggingface平台上的CodeI/O合集资源页，我们以蓝色区块高亮标注您当前所处的位置。 **数据集** <table> <tr> <th>数据集</th> <th>链接</th> </tr> <tr> <td>CodeI/O-PythonEdu-Reasoning</td> <td style="background-color: #e6f3ff; text-align: center; vertical-align: middle;"> <a href="https://huggingface.co/datasets/hkust-nlp/CodeIO-PyEdu-Reasoning">🤗</a> </td> </tr> </table> 若您感兴趣，亦可查看我们处理后的原始数据：[hkust-nlp/CodeIO-PyEdu-Reasoning-Raw](https://huggingface.co/datasets/hkust-nlp/CodeIO-PyEdu-Reasoning-Raw)。 **模型** <table> <tr> <th rowspan="2">基础模型 / 训练方式</th> <th colspan="2">CodeI/O</th> <th colspan="2">CodeI/O++</th> </tr> <tr> <th>阶段1</th> <th>阶段2</th> <th>阶段1</th> <th>阶段2</th> </tr> <tr> <td>Qwen 2.5 7B Coder</td> <td style="text-align: center; vertical-align: middle;"><a href="https://huggingface.co/hkust-nlp/qwen2.5-7b-coder_codeio_stage1">🤗</a></td> <td style="text-align: center; vertical-align: middle;"><a href="https://huggingface.co/hkust-nlp/qwen2.5-7b-coder_codeio">🤗</a></td> <td style="text-align: center; vertical-align: middle;"><a href="https://huggingface.co/hkust-nlp/qwen2.5-7b-coder_codeio_pp_stage1">🤗</a></td> <td style="text-align: center; vertical-align: middle;"><a href="https://huggingface.co/hkust-nlp/qwen2.5-7b-coder_codeio_pp">🤗</a></td> </tr> <tr> <td>LLaMA 3.1 8B</td> <td style="text-align: center; vertical-align: middle;"><a href="https://huggingface.co/hkust-nlp/llama3.1-8b_codeio_stage1">🤗</a></td> <td style="text-align: center; vertical-align: middle;"><a href="https://huggingface.co/hkust-nlp/llama3.1-8b_codeio">🤗</a></td> <td style="text-align: center; vertical-align: middle;"><a href="https://huggingface.co/hkust-nlp/llama3.1-8b_codeio_pp_stage1">🤗</a></td> <td style="text-align: center; vertical-align: middle;"><a href="https://huggingface.co/hkust-nlp/llama3.1-8b_codeio_pp">🤗</a></td> </tr> <tr> <td>DeepSeek v2 Lite Coder</td> <td style="text-align: center; vertical-align: middle;"><a href="https://huggingface.co/hkust-nlp/dsv2-lite-coder_codeio_stage1">🤗</a></td> <td style="text-align: center; vertical-align: middle;"><a href="https://huggingface.co/hkust-nlp/dsv2-lite-coder_codeio">🤗</a></td> <td style="text-align: center; vertical-align: middle;"><a href="https://huggingface.co/hkust-nlp/dsv2-lite-coder_codeio_pp_stage1">🤗</a></td> <td style="text-align: center; vertical-align: middle;"><a href="https://huggingface.co/hkust-nlp/dsv2-lite-coder_codeio_pp">🤗</a></td> </tr> </table> **引用格式** 若您认为这些资源对您的研究有所帮助，请按如下格式引用： @article{li2025codeio, title={CodeI/O: Condensing Reasoning Patterns via Code Input-Output Prediction}, author={Li, Junlong and Guo, Daya and Yang, Dejian and Xu, Runxin and Wu, Yu and He, Junxian}, journal={arXiv preprint arXiv:2502.07316}, year={2025} }

搜集汇总

背景与挑战

背景概述

该数据集名为CodeI/O-PythonEdu-Reasoning，属于CodeI/O系列，旨在通过代码输入-输出预测来压缩推理模式。它由hkust-nlp发布，采用Apache License 2.0许可，更新于2025年6月18日，大小为11.23GB。