[model_cards] Add new German Europeana BERT models (#2805)

* [model_cards] New German Europeana BERT models from dbmdz

* [model_cards] Update German Europeana BERT models from dbmdz

model_cards/dbmdz/bert-base-german-europeana-cased/README.md

@@ -0,0 +1,61 @@
+---
+language: german
+tags:
+  - "historic german"
+---
+
+# 🤗 + 📚 dbmdz BERT models
+
+In this repository the MDZ Digital Library team (dbmdz) at the Bavarian State
+Library open sources German Europeana BERT models 🎉
+
+# German Europeana BERT
+
+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).
+
+## Model weights
+
+Currently only PyTorch-[Transformers](https://github.com/huggingface/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`](https://cdn.huggingface.co/dbmdz/bert-base-german-europeana-cased/config.json)   • [`pytorch_model.bin`](https://cdn.huggingface.co/dbmdz/bert-base-german-europeana-cased/pytorch_model.bin)   • [`vocab.txt`](https://cdn.huggingface.co/dbmdz/bert-base-german-europeana-cased/vocab.txt)
+
+## Results
+
+For results on Historic NER, please refer to [this repository](https://github.com/stefan-it/europeana-bert).
+
+## Usage
+
+With Transformers >= 2.3 our German Europeana BERT models can be loaded like:
+
+```python
+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](https://huggingface.co/dbmdz).
+
+# Contact (Bugs, Feedback, Contribution and more)
+
+For questions about our BERT models just open an issue
+[here](https://github.com/dbmdz/berts/issues/new) 🤗
+
+# 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 🤗

model_cards/dbmdz/bert-base-german-europeana-uncased/README.md

@@ -0,0 +1,61 @@
+---
+language: german
+tags:
+  - "historic german"
+---
+
+# 🤗 + 📚 dbmdz BERT models
+
+In this repository the MDZ Digital Library team (dbmdz) at the Bavarian State
+Library open sources German Europeana BERT models 🎉
+
+# German Europeana BERT
+
+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).
+
+## Model weights
+
+Currently only PyTorch-[Transformers](https://github.com/huggingface/transformers)
+compatible weights are available. If you need access to TensorFlow checkpoints,
+please raise an issue!
+
+| Model                                      | Downloads
+| ------------------------------------------ | ---------------------------------------------------------------------------------------------------------------
+| `dbmdz/bert-base-german-europeana-uncased` | [`config.json`](https://cdn.huggingface.co/dbmdz/bert-base-german-europeana-uncased/config.json) • [`pytorch_model.bin`](https://cdn.huggingface.co/dbmdz/bert-base-german-europeana-uncased/pytorch_model.bin) • [`vocab.txt`](https://cdn.huggingface.co/dbmdz/bert-base-german-europeana-uncased/vocab.txt)
+
+## Results
+
+For results on Historic NER, please refer to [this repository](https://github.com/stefan-it/europeana-bert).
+
+## Usage
+
+With Transformers >= 2.3 our German Europeana BERT models can be loaded like:
+
+```python
+from transformers import AutoModel, AutoTokenizer
+
+tokenizer = AutoTokenizer.from_pretrained("dbmdz/bert-base-german-europeana-uncased")
+model = AutoModel.from_pretrained("dbmdz/bert-base-german-europeana-uncased")
+```
+
+# Huggingface model hub
+
+All models are available on the [Huggingface model hub](https://huggingface.co/dbmdz).
+
+# Contact (Bugs, Feedback, Contribution and more)
+
+For questions about our BERT models just open an issue
+[here](https://github.com/dbmdz/berts/issues/new) 🤗
+
+# 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 🤗