
# 🤗 + 📚 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 🤗

{"language": "de", "license": "mit", "tags": ["historic german"]}
transformers pytorch tf jax bert historic german de license:mit endpoints_compatible region:us
TAGS
#transformers #pytorch #tf #jax #bert #historic german #de #license-mit #endpoints_compatible #region-us 

+ 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
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!



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:


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


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



TAGS
#transformers #pytorch #tf #jax #bert #historic german #de #license-mit #endpoints_compatible #region-us 

TAGS
#transformers #pytorch #tf #jax #bert #historic german #de #license-mit #endpoints_compatible #region-us 
