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---
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base_model: Qwen/Qwen2.5-32B-Instruct
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library_name: transformers
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model_name: step-conditional-control
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tags:
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- generated_from_trainer
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- trl
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- sft
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license: apache-2.0
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language:
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- zho
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- eng
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- fra
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- spa
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- por
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- deu
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- ita
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- rus
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- jpn
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- kor
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- vie
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- tha
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- ara
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---
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# Model Summary
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- **Repository:** [simplescaling/s1](https://github.com/simplescaling/s1)
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- **Paper:** https://arxiv.org/abs/2501.19393
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# Use
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This is an older step-conditional control model for our paper used only for the Discussion section. You can evaluate using the information [here](https://github.com/simplescaling/s1?tab=readme-ov-file#evaluation).
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# Training information
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[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="150" height="24"/>](https://wandb.ai/hashimoto-group/o1/runs/rkflww8e)
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- TRL: 0.13.0
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- Transformers: 4.48.0
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- Pytorch: 2.3.1
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- Datasets: 3.0.1
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- Tokenizers: 0.21.0
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# Citation
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```bibtex
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@misc{muennighoff2025s1simpletesttimescaling,
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title={s1: Simple test-time scaling},
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author={Niklas Muennighoff and Zitong Yang and Weijia Shi and Xiang Lisa Li and Li Fei-Fei and Hannaneh Hajishirzi and Luke Zettlemoyer and Percy Liang and Emmanuel Candès and Tatsunori Hashimoto},
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year={2025},
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eprint={2501.19393},
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archivePrefix={arXiv},
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primaryClass={cs.CL},
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url={https://arxiv.org/abs/2501.19393},
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}
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``` |
