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  # ✨ ArcherCodeR
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  <div>
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- 🏹️ Reinforcement Learning for Smarter 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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  [![Model](https://img.shields.io/badge/Model-fcd022?style=for-the-badge&logo=huggingface&logoColor=000&labelColor)](https://huggingface.co/wizardII/ArcherCodeR-1.5B)
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  [![Data](https://img.shields.io/badge/Data-fcd022?style=for-the-badge&logo=huggingface&logoColor=000&labelColor)](https://huggingface.co/datasets/wizardII/ArcherCodeR-Dataset)
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  [![Wandb](https://img.shields.io/badge/Wandb-000000?style=for-the-badge&logo=Wandb&logoColor=000&labelColor)](https://wandb.ai/wangjkpkucs-peking-university/ArcherCodeR?nw=nwuserwangjkpkucs)
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-
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- </div>
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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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  - [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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- ## Technical Report
 
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- The technical report will be released soon.
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- ## Citation
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- Please cite the following:
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- ```bibtex
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- @misc{archercoder2025,
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- title={ArcherCodeR},
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- author={Jiakang Wang},
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- note={Blog},
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- year={2025}
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- }
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- ```
 
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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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+
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  </div>
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  <div>
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  <br>
 
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  [![Model](https://img.shields.io/badge/Model-fcd022?style=for-the-badge&logo=huggingface&logoColor=000&labelColor)](https://huggingface.co/wizardII/ArcherCodeR-1.5B)
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  [![Data](https://img.shields.io/badge/Data-fcd022?style=for-the-badge&logo=huggingface&logoColor=000&labelColor)](https://huggingface.co/datasets/wizardII/ArcherCodeR-Dataset)
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  [![Wandb](https://img.shields.io/badge/Wandb-000000?style=for-the-badge&logo=Wandb&logoColor=000&labelColor)](https://wandb.ai/wangjkpkucs-peking-university/ArcherCodeR?nw=nwuserwangjkpkucs)
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+ [![知乎](https://img.shields.io/badge/知乎-0084FF?style=for-the-badge&logo=zhihu&logoColor=white)](https://zhuanlan.zhihu.com/p/xxx)
 
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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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  - [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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+ ## Technical Report
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+ The technical report will be released soon.
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