Update README.md

README.md

@@ -35,7 +35,7 @@ Dynamic-TinyBERT has been fine-tuned for the NLP task of question answering, tra
 | Version | 1 | 
 | Type | NLP - Question Answering | 
 | Architecture | "For our Dynamic-TinyBERT model we use the architecture of TinyBERT6L: a small BERT model with 6 layers, a hidden size of 768, a feed forward size of 3072 and 12 heads." [Guskin et al. (2021)](https://gyuwankim.github.io/publication/dynamic-tinybert/poster.pdf) |
-| Paper or Other Resources | Paper: [Guskin et al. (2021)](https://neurips2021-nlp.github.io/papers/16/CameraReady/Dynamic_TinyBERT_NLSP2021_camera_ready.pdf) and Poster: [Guskin et al. (2021)](https://gyuwankim.github.io/publication/dynamic-tinybert/poster.pdf) | 
+| Paper or Other Resources | [Paper](https://neurips2021-nlp.github.io/papers/16/CameraReady/Dynamic_TinyBERT_NLSP2021_camera_ready.pdf); [Poster](https://gyuwankim.github.io/publication/dynamic-tinybert/poster.pdf); [GitHub Repo](https://github.com/IntelLabs/Model-Compression-Research-Package) | 
 | License | Apache 2.0 |
 | Questions or Comments | [Community Tab](https://huggingface.co/Intel/dynamic_tinybert/discussions) and [Intel Developers Discord](https://discord.gg/rv2Gp55UJQ)|