metadata
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:
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 = '讘砖谞转 1948 讛砖诇讬诐 讗驻专讬诐 拽讬砖讜谉 讗转 诇讬诪讜讚讬讜 讘驻讬住讜诇 诪转讻转 讜讘转讜诇讚讜转 讛讗诪谞讜转 讜讛讞诇 诇驻专住诐 诪讗诪专讬诐 讛讜诪讜专讬住讟讬讬诐'
print(model.predict([sentence], tokenizer))
Output:
[
[
[ "[CLS]" ],
[ "讘","砖谞转" ],
[ "1948" ],
[ "讛砖诇讬诐" ],
[ "讗驻专讬诐" ],
[ "拽讬砖讜谉" ],
[ "讗转" ],
[ "诇讬诪讜讚讬讜" ],
[ "讘","驻讬住讜诇" ],
[ "诪转讻转" ],
[ "讜讘","转讜诇讚讜转" ],
[ "讛","讗诪谞讜转" ],
[ "讜","讛讞诇" ],
[ "诇驻专住诐" ],
[ "诪讗诪专讬诐" ],
[ "讛讜诪讜专讬住讟讬讬诐" ],
[ "[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: 
This work is licensed under a Creative Commons Attribution 4.0 International License.
