readme: add new DistilBERT-related sections

README.md

@@ -4,3 +4,51 @@ license: mit
 tags:
   - "historic german"
 ---
+
+# 🤗 + 📚 dbmdz DistilBERT model
+
+In this repository the MDZ Digital Library team (dbmdz) at the Bavarian State
+Library open sources a German Europeana DistilBERT model 🎉
+
+# German Europeana DistilBERT
+
+We use the open source [Europeana newspapers](http://www.europeana-newspapers.eu/)
+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](https://github.com/stefan-it/europeana-bert).
+
+## Results
+
+For results on Historic NER, please refer to [this repository](https://github.com/stefan-it/europeana-bert).
+
+## Usage
+
+With Transformers >= 4.3 our German Europeana DistilBERT model can be loaded like:
+
+```python
+from transformers import AutoModel, AutoTokenizer
+
+model_name = "distilbert-base-german-europeana-cased"
+
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = AutoModel.from_pretrained(model_name)
+```
+
+# Huggingface model hub
+
+All other German Europeana models are available on the [Huggingface model hub](https://huggingface.co/dbmdz).
+
+# Contact (Bugs, Feedback, Contribution and more)
+
+For questions about our Europeana BERT, ELECTRA and ConvBERT models just open a new discussion
+[here](https://github.com/stefan-it/europeana-bert/discussions) 🤗
+
+# 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](https://huggingface.co/) team,
+it is possible to download both cased and uncased models from their S3 storage 🤗