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/activebus/BERT-XD_Review/README.md

README.md

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+# ReviewBERT
+
+BERT (post-)trained from review corpus to understand sentiment, options and various e-commence aspects.  
+Please visit https://github.com/howardhsu/BERT-for-RRC-ABSA for details.  
+
+`BERT-XD_Review` is a cross-domain (beyond just `laptop` and `restaurant`) language model, where each example is from a single product / restaurant with the same rating, post-trained (fine-tuned) on a combination of 5-core Amazon reviews and all Yelp data, expected to be 22 G in total. It is trained for 4 epochs on `bert-base-uncased`.
+The preprocessing code [here](https://github.com/howardhsu/BERT-for-RRC-ABSA/transformers).
+
+## Model Description
+
+The original model is from `BERT-base-uncased`.  
+Models are post-trained from [Amazon Dataset](http://jmcauley.ucsd.edu/data/amazon/) and [Yelp Dataset](https://www.yelp.com/dataset/challenge/).  
+
+
+## Instructions
+Loading the post-trained weights are as simple as, e.g., 
+
+```python
+import torch
+from transformers import AutoModel, AutoTokenizer
+
+tokenizer = AutoTokenizer.from_pretrained("activebus/BERT-XD_Review")
+model = AutoModel.from_pretrained("activebus/BERT-XD_Review")
+
+```
+
+
+## Evaluation Results
+
+Check our [NAACL paper](https://www.aclweb.org/anthology/N19-1242.pdf) 
+`BERT_Review` is expected to have similar performance on domain-specific tasks (such as aspect extraction) as `BERT-DK`, but much better on general tasks such as aspect sentiment classification (different domains mostly share similar sentiment words).
+
+
+## Citation
+If you find this work useful, please cite as following.
+```
+@inproceedings{xu_bert2019,
+    title = "BERT Post-Training for Review Reading Comprehension and Aspect-based Sentiment Analysis",
+    author = "Xu, Hu and Liu, Bing and Shu, Lei and Yu, Philip S.",
+    booktitle = "Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics",
+    month = "jun",
+    year = "2019",
+}
+```