Update README.md

README.md

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 license: mit
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+
+This is the 3 MB compressed version of GraphCodeBERT that has been fine-tuned for the Vulnerability Prediction task using [Devign](https://sites.google.com/view/devign) dataset.
+
+The compression is based on our ASE 2022 paper named ["**Compressing Pre-trained Models of Code into 3 MB**"](https://arxiv.org/abs/2208.07120). 
+
+If you are interested in using this model, please check our **GitHub repository: https://github.com/soarsmu/Compressor.git**. If you use the model or any code from our repo in your paper, please kindly cite:
+```
+@inproceedings{shi2022compressing,
+  author = {Shi, Jieke and Yang, Zhou and Xu, Bowen and Kang, Hong Jin and Lo, David},
+  title = {Compressing Pre-Trained Models of Code into 3 MB},
+  year = {2023},
+  isbn = {9781450394758},
+  publisher = {Association for Computing Machinery},
+  address = {New York, NY, USA},
+  url = {https://doi.org/10.1145/3551349.3556964},
+  doi = {10.1145/3551349.3556964},
+  booktitle = {Proceedings of the 37th IEEE/ACM International Conference on Automated Software Engineering},
+  articleno = {24},
+  numpages = {12},
+  keywords = {Pre-Trained Models, Model Compression, Genetic Algorithm},
+  location = {Rochester, MI, USA},
+  series = {ASE '22}
+}
+```