Instructions to use simplescaling/s1-32B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Inference
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Download README.md from simplescaling/s1-32B: direct link, hf CLI and curl.
- Browser
- Download file 1.65 kB
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https://huggingface.co/simplescaling/s1-32B/resolve/main/README.md
- Command line
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hf download hf://simplescaling/s1-32B/README.md
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curl -L -o README.md https://huggingface.co/simplescaling/s1-32B/resolve/main/README.md
1.65 kB
| pipeline_tag: text-generation | |
| inference: true | |
| license: apache-2.0 | |
| datasets: | |
| - simplescaling/s1K | |
| **We recommend using our successor [s1.1](https://huggingface.co/simplescaling/s1.1-32B) with better performance** | |
| # Model Summary | |
| > s1 is a reasoning model finetuned from Qwen2.5-32B-Instruct on just 1,000 examples. It matches o1-preview & exhibits test-time scaling via budget forcing. | |
| - **Repository:** [simplescaling/s1](https://github.com/simplescaling/s1) | |
| - **Paper:** https://arxiv.org/abs/2501.19393 | |
| # Use | |
| The model usage is documented [here](https://github.com/simplescaling/s1?tab=readme-ov-file#inference). | |
| # Evaluation | |
| | Metric | s1-32B | s1.1-32B | o1-preview | o1 | DeepSeek-R1 | DeepSeek-R1-Distill-Qwen-32B | | |
| |---|---|---|---|---|---|---| | |
| | # examples | 1K | 1K | ? | ? | >800K | 800K | | |
| | AIME2024 | 56.7 | 56.7 | 40.0 | 74.4 | 79.8 | 72.6 | | |
| | AIME2025 I | 26.7 | 60.0 | 37.5 | ? | 65.0 | 46.1 | | |
| | MATH500 | 93.0 | 95.4 | 81.4 | 94.8 | 97.3 | 94.3 | | |
| | GPQA-Diamond | 59.6 | 63.6 | 75.2 | 77.3 | 71.5 | 62.1 | | |
| Note that s1-32B and s1.1-32B use budget forcing in this table; specifically ignoring end-of-thinking and appending "Wait" up to four times. | |
| # Citation | |
| ```bibtex | |
| @misc{muennighoff2025s1simpletesttimescaling, | |
| title={s1: Simple test-time scaling}, | |
| 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}, | |
| year={2025}, | |
| eprint={2501.19393}, | |
| archivePrefix={arXiv}, | |
| primaryClass={cs.CL}, | |
| url={https://arxiv.org/abs/2501.19393}, | |
| } | |
| ``` |