Create README.md
Browse files
README.md
ADDED
|
@@ -0,0 +1,23 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
---
|
| 2 |
+
datasets:
|
| 3 |
+
- oscar
|
| 4 |
+
language:
|
| 5 |
+
- he
|
| 6 |
+
- ar
|
| 7 |
+
---
|
| 8 |
+
# HeArBERT
|
| 9 |
+
|
| 10 |
+
A bilingual BERT for Arabic and Hebrew, pretrained on the respective parts of the OSCAR corpus.
|
| 11 |
+
|
| 12 |
+
In order to process Arabic with this model, one would have to transliterate it to Hebrew script. The code for doing so is available on the [preprocessing](./preprocessing.py) file and can be used as follows:
|
| 13 |
+
|
| 14 |
+
```python
|
| 15 |
+
from transformers import AutoTokenizer
|
| 16 |
+
from preprocessing import transliterate_arabic_to_hebrew
|
| 17 |
+
|
| 18 |
+
tokenizer = AutoTokenizer.from_pretrained("aviadrom/HeArBERT")
|
| 19 |
+
|
| 20 |
+
text_ar = "مرحبا"
|
| 21 |
+
text_he = transliterate_arabic_to_hebrew(text_ar)
|
| 22 |
+
tokenizer(text_he)
|
| 23 |
+
```
|