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/huawei-noah/TinyBERT_General_4L_312D/README.md

README.md

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+TinyBERT: Distilling BERT for Natural Language Understanding
+======== 
+TinyBERT is 7.5x smaller and 9.4x faster on inference than BERT-base and achieves competitive performances in the tasks of natural language understanding. It performs a novel transformer distillation at both the pre-training and task-specific learning stages. In general distillation, we use the original BERT-base without fine-tuning as the teacher and a large-scale text corpus as the learning data. By performing the Transformer distillation on the text from general domain, we obtain a general TinyBERT which provides a good initialization for the task-specific distillation. We here provide the general TinyBERT for your tasks at hand.
+
+For more details about the techniques of TinyBERT, refer to our paper:
+[TinyBERT: Distilling BERT for Natural Language Understanding](https://arxiv.org/abs/1909.10351)
+
+
+Citation
+========
+If you find TinyBERT useful in your research, please cite the following paper:
+```
+@article{jiao2019tinybert,
+  title={Tinybert: Distilling bert for natural language understanding},
+  author={Jiao, Xiaoqi and Yin, Yichun and Shang, Lifeng and Jiang, Xin and Chen, Xiao and Li, Linlin and Wang, Fang and Liu, Qun},
+  journal={arXiv preprint arXiv:1909.10351},
+  year={2019}
+}
+```