🤗 + 📚 dbmdz BERT model
In this repository the MDZ Digital Library team (dbmdz) at the Bavarian State
Library open sources French Europeana BERT models 🎉
French Europeana BERT
We extracted all French texts using the language metadata attribute from the Europeana corpus.
The resulting corpus has a size of 63GB and consists of 11,052,528,456 tokens.
Based on the metadata information, texts from the 18th - 20th century are mainly included in the
training corpus.
Detailed information about the data and pretraining steps can be found in
this repository.
Model weights
BERT model weights for PyTorch and TensorFlow are available.
- French Europeana BERT:
dbmdz/bert-base-french-europeana-cased - model hub page
Results
For results on Historic NER, please refer to
this repository.
Usage
With Transformers >= 2.3 our French Europeana BERT model can be loaded like:
1from transformers import AutoModel, AutoTokenizer
2tokenizer = AutoTokenizer.from_pretrained("dbmdz/bert-base-french-europeana-cased")
3model = AutoModel.from_pretrained("dbmdz/bert-base-french-europeana-cased")
Huggingface model hub
All models are available on the Huggingface model hub.
Contact (Bugs, Feedback, Contribution and more)
For questions about our BERT model just open an issue
here 🤗
Acknowledgments
Research supported with Cloud TPUs from Google's TensorFlow Research Cloud (TFRC).
Thanks for providing access to the TFRC ❤️
Thanks to the generous support from the Hugging Face team,
it is possible to download our model from their S3 storage 🤗
