---
library_name: litert
base_model: timm/eva_giant_patch14_560.m30m_ft_in22k_in1k
license: mit
tags:
  - vision
  - image-classification
  - timm
datasets:
  - imagenet-1k
---

# eva_giant_patch14_560.m30m_ft_in22k_in1k

Converted TIMM image classification model for LiteRT.

- Source architecture: `eva_giant_patch14_560`
- Source checkpoint: `timm/eva_giant_patch14_560.m30m_ft_in22k_in1k`
- File: `model.tflite`
- Runtime target: CPU only. GPU delegation is not expected for this converted file.
- Input: `float32` tensor in NCHW layout, shape `[1, 3, 560, 560]`
- Output: ImageNet-1K logits, shape `[1, 1000]`
- Converted artifact size: 3.78 GiB
- Weight storage: `buffer_offset`

## Model Details

- **Model Type:** Image classification / feature backbone
- **Model Stats:**
  - Params (M): 1014.4
  - GMACs: 1906.8
  - Activations (M): 2577.2
  - Image size: 560 x 560
- **Papers:**
  - EVA: Exploring the Limits of Masked Visual Representation Learning at Scale: https://arxiv.org/abs/2211.07636
- **Pretrain Dataset:**
  - Merged-30M
  - ImageNet-22k
- **Dataset:** ImageNet-1k
- **Original:**
  - https://github.com/baaivision/EVA
  - https://huggingface.co/BAAI/EVA

## Citation

```bibtex
@article{EVA,
  title={EVA: Exploring the Limits of Masked Visual Representation Learning at Scale},
  author={Fang, Yuxin and Wang, Wen and Xie, Binhui and Sun, Quan and Wu, Ledell and Wang, Xinggang and Huang, Tiejun and Wang, Xinlong and Cao, Yue},
  journal={arXiv preprint arXiv:2211.07636},
  year={2022}
}
```
```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}}
}
```