Migrate model card from transformers-repo

Read announcement at https://discuss.huggingface.co/t/announcement-all-model-cards-will-be-migrated-to-hf-co-model-repos/2755
Original file history: https://github.com/huggingface/transformers/commits/master/model_cards/cimm-kzn/endr-bert/README.md

README.md

@@ -0,0 +1,47 @@
+---
+language:
+- ru
+- en
+---
+
+## EnDR-BERT
+
+  EnDR-BERT - Multilingual, Cased, which pretrained on the english collection of consumer comments on drug administration from [2]. Pre-training was based on the [original BERT code](https://github.com/google-research/bert) provided by Google. In particular, Multi-BERT was for used for initialization and all the parameters are the same as in Multi-BERT. Training details are described in our paper. \
+    link: https://yadi.sk/d/-PTn0xhk1PqvgQ
+
+ 
+  ## Citing & Authors
+
+  If you find this repository helpful, feel free to cite our publication:
+
+  [1] Tutubalina E, Alimova I, Miftahutdinov Z, et al. The Russian Drug Reaction Corpus and Neural Models for Drug Reactions and Effectiveness Detection in User Reviews.//Bioinformatics. - 2020. 
+
+     preprint: https://arxiv.org/abs/2004.03659
+ ```
+ @article{10.1093/bioinformatics/btaa675,
+     author = {Tutubalina, Elena and Alimova, Ilseyar and Miftahutdinov, Zulfat and Sakhovskiy, Andrey and Malykh, Valentin and Nikolenko, Sergey},
+     title = "{The Russian Drug Reaction Corpus and Neural Models for Drug Reactions and Effectiveness Detection in User Reviews}",
+     journal = {Bioinformatics},
+     year = {2020},
+     month = {07},
+     issn = {1367-4803},
+     doi = {10.1093/bioinformatics/btaa675},
+     url = {https://doi.org/10.1093/bioinformatics/btaa675},
+     note = {btaa675},
+     eprint = {https://academic.oup.com/bioinformatics/advance-article-pdf/doi/10.1093/bioinformatics/btaa675/33539752/btaa675.pdf},
+ } 
+ ```
+ [2] Tutubalina, EV and Miftahutdinov, Z Sh and Nugmanov, RI and Madzhidov, TI and Nikolenko, SI and Alimova, IS and Tropsha, AE Using semantic analysis of texts for the identification of drugs with similar therapeutic effects.//Russian Chemical Bulletin. – 2017. – Т. 66. – №. 11. – С. 2180-2189.
+    [link to paper](https://www.researchgate.net/profile/Elena_Tutubalina/publication/323751823_Using_semantic_analysis_of_texts_for_the_identification_of_drugs_with_similar_therapeutic_effects/links/5bf7cfc3299bf1a0202cbc1f/Using-semantic-analysis-of-texts-for-the-identification-of-drugs-with-similar-therapeutic-effects.pdf)
+ ```
+ @article{tutubalina2017using,
+     title={Using semantic analysis of texts for the identification of drugs with similar therapeutic effects},
+     author={Tutubalina, EV and Miftahutdinov, Z Sh and Nugmanov, RI and Madzhidov, TI and Nikolenko, SI and Alimova, IS and Tropsha, AE},
+     journal={Russian Chemical Bulletin},
+     volume={66},
+     number={11},
+     pages={2180--2189},
+     year={2017},
+     publisher={Springer}
+ }
+ ```