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--- |
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pipeline_tag: text-generation |
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inference: true |
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license: apache-2.0 |
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datasets: |
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- simplescaling/s1K |
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base_model: |
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- Qwen/Qwen2.5-0.5B-Instruct |
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library_name: transformers |
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language: |
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- ar |
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- de |
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- en |
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- es |
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- fr |
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- it |
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- ja |
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- ko |
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- pt |
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- ru |
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- th |
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- vi |
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- zh |
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--- |
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# Model Summary |
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> s1-0.5B is a reasoning model finetuned from Qwen2.5-0.5B-Instruct on just 1,000 examples. This model was created simply to test the process used to train the original S1 cited below using consumer grade GPUs. |
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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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The model usage is documented [here](https://github.com/simplescaling/s1?tab=readme-ov-file#inference). |
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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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``` |
