---
license: cc-by-4.0
language:
- he
inference: false
---
# DictaBERT: A State-of-the-Art BERT Suite for Modern Hebrew

State-of-the-art language model for Hebrew, as released [here](link to arxiv).

This is the fine-tuned model for the prefix segmentation task.  

Sample usage:

```python
from transformers import AutoModel, AutoTokenizer

tokenizer = AutoTokenizer.from_pretrained('dicta-il/dictabert-seg')
model = AutoModel.from_pretrained('dicta-il/dictabert-seg', trust_remote_code=True)

model.eval()

sentence = 'בשנת 1948 השלים אפרים קישון את לימודיו בפיסול מתכת ובתולדות האמנות והחל לפרסם מאמרים הומוריסטיים'
print(model.predict([sentence], tokenizer))
```

Output:
```json
[
	[
		[ "[CLS]" ],
		[ "ב","שנת" ],
		[ "1948" ],
		[ "השלים" ],
		[ "אפרים" ],
		[ "קישון" ],
		[ "את" ],
		[ "לימודיו" ],
		[ "ב","פיסול" ],
		[ "מתכת" ],
		[ "וב","תולדות" ],
		[ "ה","אמנות" ],
		[ "ו","החל" ],
		[ "לפרסם" ],
		[ "מאמרים" ],
		[ "הומוריסטיים" ],
		[ "[SEP]" ]
	]
]
```


## Citation

If you use DictaBERT in your research, please cite ```DictaBERT: A State-of-the-Art BERT Suite for Modern Hebrew```

**BibTeX:**

To add

## License

Shield: [![CC BY 4.0][cc-by-shield]][cc-by]

This work is licensed under a
[Creative Commons Attribution 4.0 International License][cc-by].

[![CC BY 4.0][cc-by-image]][cc-by]

[cc-by]: http://creativecommons.org/licenses/by/4.0/
[cc-by-image]: https://i.creativecommons.org/l/by/4.0/88x31.png
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