s1-32B

s1 is an inference model fine-tuned based on Qwen2.5-32B-Instruct, trained with only 1,000 samples.

CommonProductProductivityText GenerationInference Model

s1 is an inference model that focuses on achieving efficient text generation capabilities with a limited set of samples. It scales during testing using budget enforcement techniques, capable of matching the performance of o1-preview. Developed by Niklas Muennighoff et al., the related research is published on arXiv. The model employs Safetensors technology, boasts 32.8 billion parameters, and supports text generation tasks. Its main advantage lies in achieving high-quality reasoning through a limited number of samples, making it suitable for scenarios requiring efficient text generation.

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