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Bayerische Staatsbibliothek non-profit
1 team member Β· 35 models

πŸ€— + πŸ“š dbmdz BERT models

In this repository the MDZ Digital Library team (dbmdz) at the Bavarian State Library open sources German Europeana BERT models πŸŽ‰

German Europeana BERT

We use the open source Europeana newspapers that were provided by The European Library. The final training corpus has a size of 51GB and consists of 8,035,986,369 tokens.

Detailed information about the data and pretraining steps can be found in this repository.

Model weights

Currently only PyTorch-Transformers compatible weights are available. If you need access to TensorFlow checkpoints, please raise an issue!

Model Downloads
dbmdz/bert-base-german-europeana-cased config.json β€’ pytorch_model.bin β€’ vocab.txt

Results

For results on Historic NER, please refer to this repository.

Usage

With Transformers >= 2.3 our German Europeana BERT models can be loaded like:

from transformers import AutoModel, AutoTokenizer

tokenizer = AutoTokenizer.from_pretrained("dbmdz/bert-base-german-europeana-cased")
model = AutoModel.from_pretrained("dbmdz/bert-base-german-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 models just open an issue here πŸ€—

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 both cased and uncased models from their S3 storage πŸ€—