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--- |
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license: mit |
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language: |
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- en |
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tags: |
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- code |
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pretty_name: ' ArcherCodeR' |
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size_categories: |
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- 1K<n<10K |
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task_categories: |
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- text-generation |
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viewer: false |
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--- |
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<div align="center"> |
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# ✨ ArcherCodeR |
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<div> |
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🏹️ Reinforcement Learning for Enhanced Code Reasoning in LLMs 🎯 |
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</div> |
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</div> |
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<div> |
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<br> |
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<div align="center"> |
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[](https://github.com/wizard-III/ArcherCodeR) |
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[](https://huggingface.co/wizardII/ArcherCodeR-1.5B) |
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[](https://huggingface.co/datasets/wizardII/ArcherCodeR-Dataset) |
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[](https://wandb.ai/wangjkpkucs-peking-university/ArcherCodeR?nw=nwuserwangjkpkucs) |
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[](https://zhuanlan.zhihu.com/p/1918765619614057424) |
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</div> |
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## Overview |
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[`ArcherCodeR-Dataset`](https://huggingface.co/datasets/wizardII/ArcherCodeR-Dataset) is **a dataset of verifiable, challenging, and diverse coding questions (6.7K)**. This dataset is used to train the **`ArcherCodeR`** model series, which consists of code reasoning models trained using large-scale rule-based reinforcement learning with carefully designed datasets and training recipes. |
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We select, clean, and curate coding problems from open-source datasets, including |
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- [agentica-org/DeepScaleR-Preview-Dataset](https://huggingface.co/datasets/agentica-org/DeepScaleR-Preview-Dataset) |
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- [deepmind/code_contests](https://huggingface.co/datasets/deepmind/code_contests) |
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- [open-r1/codeforces](https://huggingface.co/datasets/open-r1/codeforces) |
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### 🔍 Key Notes: |
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- Both code_contests (DeepMind) and codeforces (Open-r1) datasets include regenerated test cases to mitigate false positives. |
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- Significant prompt duplication exists across sources. When duplicates occur, code_contests or codeforces data takes priority. |
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For more details on data processing, please refer to our [Zhihu article](https://zhuanlan.zhihu.com/p/1918765619614057424). |
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## Technical Report |
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The technical report will be released soon. |
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