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--- |
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license: cc-by-4.0 |
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language: |
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- he |
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--- |
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# DictaBERT: A State-of-the-Art BERT Suite for Modern Hebrew |
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State-of-the-art language model for Hebrew, released [here](https://arxiv.org/abs/2308.16687). |
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This is the base model pretrained with the masked-language-modeling objective. |
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For the bert-base models for other tasks, see [here](https://huggingface.co/collections/dicta-il/dictabert-6588e7cc08f83845fc42a18b). |
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Sample usage: |
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```python |
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from transformers import AutoModelForMaskedLM, AutoTokenizer |
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tokenizer = AutoTokenizer.from_pretrained('dicta-il/dictabert') |
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model = AutoModelForMaskedLM.from_pretrained('dicta-il/dictabert') |
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model.eval() |
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sentence = '讘砖谞转 1948 讛砖诇讬诐 讗驻专讬诐 拽讬砖讜谉 讗转 [MASK] 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' |
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output = model(tokenizer.encode(sentence, return_tensors='pt')) |
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# the [MASK] is the 7th token (including [CLS]) |
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import torch |
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top_2 = torch.topk(output.logits[0, 7, :], 2)[1] |
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print('\n'.join(tokenizer.convert_ids_to_tokens(top_2))) # should print 诪讞拽专讜 / 讛转诪讞讜转讜 |
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``` |
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## Citation |
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If you use DictaBERT in your research, please cite ```DictaBERT: A State-of-the-Art BERT Suite for Modern Hebrew``` |
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**BibTeX:** |
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```bibtex |
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@misc{shmidman2023dictabert, |
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title={DictaBERT: A State-of-the-Art BERT Suite for Modern Hebrew}, |
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author={Shaltiel Shmidman and Avi Shmidman and Moshe Koppel}, |
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year={2023}, |
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eprint={2308.16687}, |
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archivePrefix={arXiv}, |
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primaryClass={cs.CL} |
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} |
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``` |
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## License |
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Shield: [![CC BY 4.0][cc-by-shield]][cc-by] |
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This work is licensed under a |
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[Creative Commons Attribution 4.0 International License][cc-by]. |
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[![CC BY 4.0][cc-by-image]][cc-by] |
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[cc-by]: http://creativecommons.org/licenses/by/4.0/ |
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[cc-by-image]: https://i.creativecommons.org/l/by/4.0/88x31.png |
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[cc-by-shield]: https://img.shields.io/badge/License-CC%20BY%204.0-lightgrey.svg |
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