Instructions to use BSC-LT/MrBERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use BSC-LT/MrBERT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="BSC-LT/MrBERT")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("BSC-LT/MrBERT") model = AutoModelForMaskedLM.from_pretrained("BSC-LT/MrBERT") - Notebooks
- Google Colab
- Kaggle
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### Citation
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archivePrefix={arXiv},
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primaryClass={cs.CL},
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url={https://arxiv.org/abs/2602.21379},
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### Citation
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@article{tamayo2026mrbert,
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title={MrBERT: Modern Multilingual Encoders via Vocabulary, Domain, and Dimensional Adaptation},
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author={Tamayo, Daniel and Lacunza, I{\~n}aki and Rivera-Hidalgo, Paula and Da Dalt, Severino and Aula-Blasco, Javier and Gonzalez-Agirre, Aitor and Villegas, Marta},
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journal={arXiv preprint arXiv:2602.21379},
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year={2026}
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}
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```
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