SI-Lab/StepCountQA-SFT
StepCountQA-SFT StepCountQA-SFT is a multimodal supervised fine-tuning (SFT) dataset for visual object counting with step-by-step reasoning. Built from PixMo-Count and PixMo-Points. Used to fine-tune vision-language models (e.g., Qwen2.5-VL) on visual counting with chain-of-thought reasoning. Dataset Statistics Split Entries Parquet Shards Approx. Size train 1,005,633 126 ~226 GB Data Format Each entry contains: { "conversations":… See the full description on the dataset page: https://huggingface.co/datasets/SI-Lab/StepCountQA-SFT.
| Author / organization | SI-Lab |
|---|---|
| License (as declared) | odc-by |
| Downloads | 193 (as reported by Hugging Face) |
| Likes | 2 |
| Created | 1 May 2026 |
| Last updated at source | 1 May 2026 |
Recent changes
- 16 Oct 2026 Description: StepCountQA-SFT StepCountQA-SFT is a multimodal supervised fine-tuning (SFT) dataset for visual object counting with step-by-step reasoning. Built from PixMo-Count and PixMo-Points. Used to fine-tune vision-language models (e.g., Qwen2.5-VL → StepCountQA-SFT StepCountQA-SFT is a multimodal supervised fine-tuning (SFT) dataset for visual object counting with step-by-step reasoning. Built from PixMo-Count and PixMo-Points. Used to fine-tune vision-language models (e.g., Qwen2.5-VL
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