8
stars
11
commits
3
repos using this model
3
linked in READMEs
Oct 28, 2024
updated
In this repository the MDZ Digital Library team (dbmdz) at the Bavarian State Library open sources a German Europeana DistilBERT model 🎉
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.
For results on Historic NER, please refer to this repository.
With Transformers >= 4.3 our German Europeana DistilBERT model can be loaded like:
from transformers import AutoModel, AutoTokenizer
model_name = "dbmdz/distilbert-base-german-europeana-cased"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModel.from_pretrained(model_name)
All other German Europeana models are available on the Huggingface model hub.
For questions about our Europeana BERT, ELECTRA and ConvBERT models just open a new discussion here 🤗
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 🤗
8
stars
11
commits
3
repos using this model
3
linked in READMEs
Oct 28, 2024
updated
In this repository the MDZ Digital Library team (dbmdz) at the Bavarian State Library open sources a German Europeana DistilBERT model 🎉
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.
For results on Historic NER, please refer to this repository.
With Transformers >= 4.3 our German Europeana DistilBERT model can be loaded like:
from transformers import AutoModel, AutoTokenizer
model_name = "dbmdz/distilbert-base-german-europeana-cased"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModel.from_pretrained(model_name)
All other German Europeana models are available on the Huggingface model hub.
For questions about our Europeana BERT, ELECTRA and ConvBERT models just open a new discussion here 🤗
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 🤗