metadata
license: apache-2.0
tags:
- self-supervised learning
- vision
- SiT
inference: false
Model description
SiT is a self-supervised learning model that combines masked image modeling and contrastive learning. The model is trained on ImageNet-1K.
Model Sources
Model Card Authors
Sara Atito, Muhammad Awais, Josef Kittler
How to use
from modeling_sit import ViTSiTForPreTraining
# reload
model = ViTSiTForPreTraining.from_pretrained("erow/SiT")
BibTeX entry and citation info
@inproceedings{atito2023sit,
title={SiT is all you need},
author={Atito, Sara and Awais, Muhammed and Nandam, Srinivasa and Kittler, Josef},
booktitle={2023 IEEE International Conference on Image Processing (ICIP)},
pages={2125--2129},
year={2023},
organization={IEEE}
}