Update README.md with SiT model information

README.md

@@ -1,3 +1,43 @@
 ---
 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
+
+- https://github.com/Sara-Ahmed/SiT
+- https://arxiv.org/abs/2104.03602
+
+
+# Model Card Authors 
+Sara Atito, Muhammad Awais, Josef Kittler
+
+# How to use
+
+```python
+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}
+}
+```