---
library_name: litert
base_model: timm/repvit_m0_9.dist_300e_in1k
tags:
  - vision
  - image-classification
datasets:
  - imagenet-1k
---
# repvit_m0_9

Converted TIMM image classification model for LiteRT.

- Source architecture: `repvit_m0_9`
- Source checkpoint: `timm/repvit_m0_9.dist_300e_in1k`
- File: `model.tflite`
- Input: `float32` tensor in NCHW layout, shape `[1, 3, 224, 224]`
- Output: ImageNet-1K logits, shape `[1, 1000]`

## Model Details

- **Model Type:** Image classification / feature backbone
- **Model Stats:**
  - Params (M): 5.5
  - GMACs: 0.8
  - Activations (M): 7.4
  - Image size: 224 x 224
- **Papers:**
  - RepViT: Revisiting Mobile CNN From ViT Perspective: https://arxiv.org/abs/2307.09283
- **Original:** https://github.com/THU-MIG/RepViT
- **Dataset:** ImageNet-1k

## Citation

```bibtex
@misc{wang2023repvit,
  title={RepViT: Revisiting Mobile CNN From ViT Perspective}, 
  author={Ao Wang and Hui Chen and Zijia Lin and Hengjun Pu and Guiguang Ding},
  year={2023},
  eprint={2307.09283},
  archivePrefix={arXiv},
  primaryClass={cs.CV}
}
```