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Datasets:
JasonShiii
/
STEP-LLM-dataset

Tasks:
Text Generation
Languages:
English
Size:
10K<n<100K
ArXiv:
Tags:
CAD
STEP
text-to-CAD
ABC-dataset
rendering
License:
Dataset card Files
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STEP-LLM-dataset
File size: 2,787 Bytes
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---
license: cc-by-4.0
task_categories:
- text-generation
language:
- en
tags:
- CAD
- STEP
- text-to-CAD
- ABC-dataset
- rendering
pretty_name: STEP-LLM Dataset
size_categories:
- 10K<n<100K
---

# STEP-LLM Dataset

Rendered multi-view images of ABC Dataset STEP files, used in our DATE 2026 paper:

**"STEP-LLM: Generating CAD STEP Models from Natural Language with Large Language Models"**

[![arXiv](https://img.shields.io/badge/arXiv-2601.12641-b31b1b.svg)](https://arxiv.org/abs/2601.12641)
[![GitHub](https://img.shields.io/badge/GitHub-STEP--LLM-blue)](https://github.com/JasonShiii/STEP-LLM)

## Dataset Contents

Rendered JPEG images of CAD models from the [ABC Dataset](https://archive.nyu.edu/handle/2451/43778) (NYU), organized by entity count. These images were used with GPT-4o to generate natural language captions for training STEP-LLM.

| Folder | Entity range | # Models | Description |
|---|---|---|---|
| `step_under500_image/` | 0–500 entities | ~20k | Used in DATE 2026 paper |
| `step_500-1000_image/` | 500–1000 entities | ~17k | Ongoing journal extension |

Each folder contains 10 per-chunk zip files (one per ABC dataset chunk `abc_0001` – `abc_0010`):
- `step_under500_image/abc_000N_step_v00_under500_image.zip` (~25 MB each)
- `step_500-1000_image/abc_000N_step_v00_500-1000.zip` (~75–85 MB each)

## Download

```python
from huggingface_hub import hf_hub_download

# Download a single chunk (under-500 entities, chunk 1)
hf_hub_download(
    repo_id="JasonShiii/STEP-LLM-dataset",
    filename="step_under500_image/abc_0001_step_v00_under500_image.zip",
    repo_type="dataset",
    local_dir="./data"
)
```

Or download all chunks:
```bash
huggingface-cli download JasonShiii/STEP-LLM-dataset --repo-type dataset --local-dir ./data
```

## Usage

These images are used in `data_preparation/captioning.ipynb` (see [GitHub repo](https://github.com/JasonShiii/STEP-LLM)) to generate GPT-4o captions, which become the natural language training inputs for STEP-LLM.

The released captions are available directly in the GitHub repo (`cad_captions_0-500.csv`, `cad_captions_500-1000.csv`) — you do not need to download these images to train or run inference with STEP-LLM.

## License

Images are derived from the [ABC Dataset](https://archive.nyu.edu/handle/2451/43778) and released under [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/).

## Citation

```bibtex
@article{shi2026step,
  title={STEP-LLM: Generating CAD STEP Models from Natural Language with Large Language Models},
  author={Shi, Xiangyu and Ding, Junyang and Zhao, Xu and Zhan, Sinong and Mohapatra, Payal
          and Quispe, Daniel and Welbeck, Kojo and Cao, Jian and Chen, Wei and Guo, Ping and others},
  journal={arXiv preprint arXiv:2601.12641},
  year={2026}
}
```