Just 1,000 ultra-curated questions with reasoning traces — selected from 59k candidates for difficulty, diversity, and quality, with traces regenerated by DeepSeek R1 in the 1.1 release. Fine-tuning Qwen2.5-32B on s1K (26 minutes on 16 H100s) plus 'budget forcing' at inference exceeded o1-preview on competition math. The LIMA of reasoning: proof that data quality can beat quantity.
| Provider | SimpleScaling |
| Category | Reasoning |
| Size | 1k Rows |
| License | Apache 2.0 |
| Downloads | n/a |
| Tags | Curated, Test-Time-Scaling, Quality-over-Quantity, R1-Traces, 2025 |
from datasets import load_dataset
ds = load_dataset("simplescaling/s1K-1.1")
Estimated VRAM to fine-tune with QLoRA (4-bit base model + LoRA adapters), using conservative defaults:
| 7B QLoRA | ~6GB VRAM |
| 13B QLoRA | ~10GB VRAM |
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