Update README.md

README.md

@@ -1,3 +1,37 @@
 ---
 license: apache-2.0
+language:
+- he
+library_name: transformers
+tags:
+- bert
 ---
+
+> Update 2023-5-23: This model is `BEREL` version 1.0. We are now happy to provide a much improved `BEREL_2.0`.
+
+
+# Introducing BEREL: BERT Embeddings for Rabbinic-Encoded Language
+
+When using BEREL, please reference:
+
+
+Avi Shmidman, Joshua Guedalia, Shaltiel Shmidman, Cheyn Shmuel Shmidman, Eli Handel, Moshe Koppel, "Introducing BEREL: BERT Embeddings for Rabbinic-Encoded Language", Aug 2022 [arXiv:2208.01875]
+
+
+
+1. Usage:
+
+```python
+from transformers import AutoTokenizer, BertForMaskedLM
+
+tokenizer = AutoTokenizer.from_pretrained('dicta-il/BEREL')
+model = BertForMaskedLM.from_pretrained('dicta-il/BEREL')
+```
+
+> NOTE: This code will **not** work and provide bad results if you use `BertTokenizer`. Please use `AutoTokenizer` or `BertTokenizerFast`.
+
+2.  Demo site:
+You can experiment with the model in a GUI interface here: https://dicta-bert-demo.netlify.app/?genre=rabbinic
+- The main part of the GUI consists of word buttons visualizing the tokenization of the sentences. Clicking on a button masks it, and then three BEREL word predictions are shown. Clicking on that bubble expands it to 10 predictions; alternatively, ctrl-clicking on that initial bubble expands to 30 predictions.
+- Ctrl-clicking adjacent word buttons combines them into a single token for the mask.
+- The edit box on top contains the input sentence; this can be modified at will, and the word-buttons will adjust as relevant.