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--- |
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language: de |
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license: mit |
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tags: |
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- "historic german" |
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--- |
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# 🤗 + 📚 dbmdz ConvBERT model |
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In this repository the MDZ Digital Library team (dbmdz) at the Bavarian State |
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Library open sources a German Europeana ConvBERT model 🎉 |
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# German Europeana ConvBERT |
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We use the open source [Europeana newspapers](http://www.europeana-newspapers.eu/) |
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that were provided by *The European Library*. The final |
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training corpus has a size of 51GB and consists of 8,035,986,369 tokens. |
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Detailed information about the data and pretraining steps can be found in |
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[this repository](https://github.com/stefan-it/europeana-bert). |
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## Results |
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For results on Historic NER, please refer to [this repository](https://github.com/stefan-it/europeana-bert). |
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## Usage |
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With Transformers >= 4.3 our German Europeana ConvBERT model can be loaded like: |
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```python |
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from transformers import AutoModel, AutoTokenizer |
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model_name = "dbmdz/convbert-base-german-europeana-cased" |
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tokenizer = AutoTokenizer.from_pretrained(model_name) |
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model = AutoModel.from_pretrained(model_name) |
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``` |
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# Huggingface model hub |
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All other German Europeana models are available on the [Huggingface model hub](https://huggingface.co/dbmdz). |
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# Contact (Bugs, Feedback, Contribution and more) |
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For questions about our Europeana BERT, ELECTRA and ConvBERT models just open a new discussion |
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[here](https://github.com/stefan-it/europeana-bert/discussions) 🤗 |
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# Acknowledgments |
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Research supported with Cloud TPUs from Google's TensorFlow Research Cloud (TFRC). |
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Thanks for providing access to the TFRC ❤️ |
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Thanks to the generous support from the [Hugging Face](https://huggingface.co/) team, |
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it is possible to download both cased and uncased models from their S3 storage 🤗 |
