This is an unofficial PyTorch implementation of EdgeViT in "EdgeViTs: Competing Light-weight CNNs on Mobile Devices with Vision Transformers", arXiv 2022.
Pretrained models will come soon.
from edgevit import EdgeViT_XXS, EdgeViT_XS, EdgeViT_S
model = EdgeViT_XXS()
inputs = torch.randn((1, 3, 224, 224))
print(model(inputs))
@article{pan2022edgevits,
title={EdgeViTs: Competing Light-weight CNNs on Mobile Devices with Vision Transformers},
author={Pan, Junting and Bulat, Adrian and Tan, Fuwen and Zhu, Xiatian and Dudziak, Lukasz and Li, Hongsheng and Tzimiropoulos, Georgios and Martinez, Brais},
journal={arXiv preprint arXiv:2205.03436},
year={2022}
}