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--- |
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license: apache-2.0 |
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language: |
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- he |
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library_name: transformers |
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tags: |
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- bert |
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--- |
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# Introducing BEREL 2.0 - New and Improved BEREL: BERT Embeddings for Rabbinic-Encoded Language |
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When using BEREL 2.0, please reference: |
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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] |
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1. Usage: |
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```python |
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from transformers import AutoTokenizer, BertForMaskedLM |
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tokenizer = AutoTokenizer.from_pretrained('dicta-il/BEREL_2.0') |
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model = BertForMaskedLM.from_pretrained('dicta-il/BEREL_2.0') |
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``` |
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> NOTE: This code will **not** work and provide bad results if you use `BertTokenizer`. Please use `AutoTokenizer` or `BertTokenizerFast`. |
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2. Demo site: |
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You can experiment with the model in a GUI interface here: https://dicta-bert-demo.netlify.app/?genre=rabbinic |
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- 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. |
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- Ctrl-clicking adjacent word buttons combines them into a single token for the mask. |
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- The edit box on top contains the input sentence; this can be modified at will, and the word-buttons will adjust as relevant. |
