|
|
--- |
|
|
license: apache-2.0 |
|
|
language: |
|
|
- he |
|
|
library_name: transformers |
|
|
tags: |
|
|
- bert |
|
|
--- |
|
|
|
|
|
# Introducing BEREL 3.0 - New and Improved BEREL: BERT Embeddings for Rabbinic-Encoded Language |
|
|
|
|
|
When using BEREL 3.0, 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_3.0') |
|
|
model = BertForMaskedLM.from_pretrained('dicta-il/BEREL_3.0') |
|
|
|
|
|
# for evaluation, disable dropout |
|
|
model.eval() |
|
|
``` |
|
|
|
|
|
> NOTE: This code will **not** work and provide bad results if you use `BertTokenizer`. Please use `AutoTokenizer` or `BertTokenizerFast`. |
|
|
|
