---
library_name: litert
base_model: timm/deit_tiny_patch16_224.fb_in1k
tags:
  - vision
  - image-classification
datasets:
  - imagenet-1k
---

# deit_tiny_patch16_224

Converted TIMM image classification model for LiteRT.

- Source architecture: deit_tiny_patch16_224
- File: model.tflite

## Model Details

- **Model Type:** Image classification / feature backbone
- **Model Stats:**
  - Params (M): 5.7
  - GMACs: 1.3
  - Activations (M): 6.0
  - Image size: 224 x 224
- **Papers:**
  - Training data-efficient image transformers & distillation through attention: https://arxiv.org/abs/2012.12877
- **Original:** https://github.com/facebookresearch/deit
- **Dataset:** ImageNet-1k

## Citation

```bibtex
@InProceedings{pmlr-v139-touvron21a,
  title =     {Training data-efficient image transformers & distillation through attention},
  author =    {Touvron, Hugo and Cord, Matthieu and Douze, Matthijs and Massa, Francisco and Sablayrolles, Alexandre and Jegou, Herve},
  booktitle = {International Conference on Machine Learning},
  pages =     {10347--10357},
  year =      {2021},
  volume =    {139},
  month =     {July}
}
```
```bibtex
@misc{rw2019timm,
  author = {Ross Wightman},
  title = {PyTorch Image Models},
  year = {2019},
  publisher = {GitHub},
  journal = {GitHub repository},
  doi = {10.5281/zenodo.4414861},
  howpublished = {\url{https://github.com/huggingface/pytorch-image-models}}
}
```