Update README.md

README.md

@@ -1,3 +1,36 @@
 ---
 license: mit
+datasets:
+- imagenet-1k
+language:
+- en
+metrics:
+- accuracy
+pipeline_tag: image-classification
+tags:
+- code
 ---
+# Matryoshka Representation Learning🪆
+_Aditya Kusupati*, Gantavya Bhatt*, Aniket Rege*, Matthew Wallingford, Aditya Sinha, Vivek Ramanujan, William Howard-Snyder, Kaifeng Chen, Sham Kakade, Prateek Jain, Ali Farhadi_
+
+GitHub: https://github.com/RAIVNLab/MRL
+
+Arxiv: https://arxiv.org/abs/2205.13147
+
+We provide pretrained models trained with [FFCV](https://github.com/libffcv/ffcv) on ImageNet-1K:
+1. `mrl` : ResNet50 __mrl__ models trained with Matryoshka loss (vanilla and efficient) with nesting starting from _d=8_ (default) and _d=16_
+2. `fixed-feature` : independently trained ResNet50 baselines at _log(d)_ granularities
+3. `resnet-family` : __mrl__ and __ff__ models trained on ResNet18/34/101
+
+## Citation
+If you find this project useful in your research, please consider citing:
+```
+@inproceedings{kusupati2022matryoshka,
+  title     = {Matryoshka Representation Learning},
+  author    = {Kusupati, Aditya and Bhatt, Gantavya and Rege, Aniket and Wallingford, Matthew and Sinha, Aditya and Ramanujan, Vivek and Howard-Snyder, William and Chen, Kaifeng and Kakade, Sham and Jain, Prateek and others},
+  title     = {Matryoshka Representation Learning.},
+  booktitle = {Advances in Neural Information Processing Systems},
+  month     = {December},
+  year      = {2022},
+}
+```