--- license: cc-by-4.0 language: - he --- # DictaBERT: A State-of-the-Art BERT Suite for Modern Hebrew State-of-the-art language model for Hebrew, released [here](https://arxiv.org/abs/2308.16687). This is the fine-tuned BERT-base model for the named-entity-recognition task. For the bert-base models for other tasks, see [here](https://huggingface.co/collections/dicta-il/dictabert-6588e7cc08f83845fc42a18b). Sample usage: ```python from transformers import pipeline oracle = pipeline('ner', model='dicta-il/dictabert-ner', aggregation_strategy='simple') # if we set aggregation_strategy to simple, we need to define a decoder for the tokenizer. Note that the last wordpiece of a group will still be emitted from tokenizers.decoders import WordPiece oracle.tokenizer.backend_tokenizer.decoder = WordPiece() sentence = 'הכי דרמטי שיש: שער של סדריק המחליף העניק לזיו אריה ניצחון שני בשלושה משחקים ועלייה מעל הקו האדום.' oracle(sentence) ``` Output: ```json [ { "entity_group": "PER", "score": "0.99978834", "word": "סדריק", "start": "22", "end": "27" }, { "entity_group": "PER", "score": "0.99994457", "word": "לזי", "start": "41", "end": "44" }, { "entity_group": "PER", "score": "0.99993944", "word": "אריה", "start": "46", "end": "50" } ] ``` ## Citation If you use DictaBERT in your research, please cite ```DictaBERT: A State-of-the-Art BERT Suite for Modern Hebrew``` **BibTeX:** ```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} } ``` ## 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 [cc-by-shield]: https://img.shields.io/badge/License-CC%20BY%204.0-lightgrey.svg