DictaBERT: A State-of-the-Art BERT Suite for Modern Hebrew
State-of-the-art language model for Hebrew, released
here
.
This is the fine-tuned model for the syntax dependency tree parsing task.
For the bert-base models for other tasks, see
here
.
Sample usage:
from transformers import AutoModel, AutoTokenizer
tokenizer = AutoTokenizer.from_pretrained('dicta-il/dictabert-syntax')
model = AutoModel.from_pretrained('dicta-il/dictabert-syntax', 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))
If you use DictaBERT in your research, please cite
DictaBERT: A State-of-the-Art BERT Suite for Modern Hebrew
BibTeX:
@misc{shmidman2023dictabert,
title={DictaBERT: A State-of-the-Art BERT Suite for Modern Hebrew},
author={Shaltiel Shmidman and Avi Shmidman and Moshe Koppel},
year={2023},
eprint={2308.16687},
archivePrefix={arXiv},
primaryClass={cs.CL}
}
Citation
If you use DictaBERT-syntax in your research, please cite
MRL Parsing without Tears: The Case of Hebrew
BibTeX:
@misc{shmidman2024mrl,
title={MRL Parsing Without Tears: The Case of Hebrew},
author={Shaltiel Shmidman and Avi Shmidman and Moshe Koppel and Reut Tsarfaty},
year={2024},
eprint={2403.06970},
archivePrefix={arXiv},
primaryClass={cs.CL}
}
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