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title: Iwin Transformer Image Classification
emoji: 🪟
colorFrom: blue
colorTo: pink
sdk: gradio
sdk_version: 6.26.0
app_file: app.py
short_description: Iwin Transformer for ImageNet image classification
python_version: "3.12"
startup_duration_timeout: 30m
---
# Iwin Transformer — ImageNet Classification
This Space demonstrates **Iwin Transformer**, a hierarchical vision transformer
that uses interleaved windows and depthwise separable convolution for efficient
global information exchange within a single module.
## Model
- **Paper**: [Iwin Transformer: Hierarchical Vision Transformer using Interleaved Windows](https://arxiv.org/abs/2507.18405)
- **Code**: [GitHub](https://github.com/cominder/Iwin-Transformer)
- **Weights**: [HuggingFace](https://huggingface.co/cominder/Iwin-Transformer)
The model is trained on ImageNet-1k (with 22k pretraining for the base variant)
and classifies images into 1000 ImageNet categories.
## Variants
| Variant | Params | Top-1 Acc | Checkpoint |
|---------|--------|-----------|------------|
| Tiny | ~28M | 81.2% | `iwin_tiny_patch4_window7_224.pth` |
| Small | ~50M | 83.5% | `iwin_small_patch4_window7_224.pth` |
| Base | ~88M | 85.2% | `iwin_base_patch4_window7_224_22kto1k.pth` |
## Citation
```bibtex
@misc{huo2025iwin,
title={Iwin Transformer: Hierarchical Vision Transformer using Interleaved Windows},
author={Simin Huo and Ning Li},
year={2025},
eprint={2507.18405},
archivePrefix={arXiv},
primaryClass={cs.CV},
url={https://arxiv.org/abs/2507.18405},
}
``` |