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Migrate model card from transformers-repo

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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

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+ ---
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+ language:
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+ - ru
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+ - en
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+ ---
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+
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+ ## EnDR-BERT
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+
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+ 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. \
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+ link: https://yadi.sk/d/-PTn0xhk1PqvgQ
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+
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+
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+ ## Citing & Authors
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+
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+ If you find this repository helpful, feel free to cite our publication:
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+
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+ [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.
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+
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+ preprint: https://arxiv.org/abs/2004.03659
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+ ```
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+ @article{10.1093/bioinformatics/btaa675,
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+ author = {Tutubalina, Elena and Alimova, Ilseyar and Miftahutdinov, Zulfat and Sakhovskiy, Andrey and Malykh, Valentin and Nikolenko, Sergey},
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+ title = "{The Russian Drug Reaction Corpus and Neural Models for Drug Reactions and Effectiveness Detection in User Reviews}",
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+ journal = {Bioinformatics},
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+ year = {2020},
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+ month = {07},
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+ issn = {1367-4803},
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+ doi = {10.1093/bioinformatics/btaa675},
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+ url = {https://doi.org/10.1093/bioinformatics/btaa675},
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+ note = {btaa675},
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+ eprint = {https://academic.oup.com/bioinformatics/advance-article-pdf/doi/10.1093/bioinformatics/btaa675/33539752/btaa675.pdf},
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+ }
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+ ```
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+ [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.
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+ [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)
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+ ```
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+ @article{tutubalina2017using,
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+ title={Using semantic analysis of texts for the identification of drugs with similar therapeutic effects},
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+ author={Tutubalina, EV and Miftahutdinov, Z Sh and Nugmanov, RI and Madzhidov, TI and Nikolenko, SI and Alimova, IS and Tropsha, AE},
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+ journal={Russian Chemical Bulletin},
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+ volume={66},
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+ number={11},
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+ pages={2180--2189},
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+ year={2017},
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+ publisher={Springer}
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+ }
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+ ```