Unlike distilbert-base-multilingual-cased, our versions give exactly the same representations produced by the original model which preserves the original accuracy.

For more information please visit our paper: Load What You Need: Smaller Versions of Multilingual BERT.

How to use

python

from transformers import AutoTokenizer, AutoModel

tokenizer = AutoTokenizer.from_pretrained("Geotrend/bert-base-en-no-cased")
model = AutoModel.from_pretrained("Geotrend/bert-base-en-no-cased")

To generate other smaller versions of multilingual transformers please visit our Github repo.

How to cite

bibtex

@inproceedings{smallermbert,
  title={Load What You Need: Smaller Versions of Mutlilingual BERT},
  author={Abdaoui, Amine and Pradel, Camille and Sigel, Grégoire},
  booktitle={SustaiNLP / EMNLP},
  year={2020}
}

Contact

Please contact amine@geotrend.fr for any question, feedback or request.