readme: ---
  language: de
  license: mit
  ---
  
  # 🤗 + 📚 dbmdz German BERT models
  
  In this repository the MDZ Digital Library team (dbmdz) at the Bavarian State
  Library open sources another German BERT models 🎉
  
  # German BERT
  
  ## Stats
  
  In addition to the recently released [German BERT](https://deepset.ai/german-bert)
  model by [deepset](https://deepset.ai/) we provide another German-language model.
  
  The source data for the model consists of a recent Wikipedia dump, EU Bookshop corpus,
  Open Subtitles, CommonCrawl, ParaCrawl and News Crawl. This results in a dataset with
  a size of 16GB and 2,350,234,427 tokens.
  
  For sentence splitting, we use [spacy](https://spacy.io/). Our preprocessing steps
  (sentence piece model for vocab generation) follow those used for training
  [SciBERT](https://github.com/allenai/scibert). The model is trained with an initial
  sequence length of 512 subwords and was performed for 1.5M steps.
  
  This release includes both cased and uncased models.
  
  ## 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
  | -------------------------------- | ---------------------------------------------------------------------------------------------------------------
  | `bert-base-german-dbmdz-cased`   | [`config.json`](https://s3.amazonaws.com/models.huggingface.co/bert/bert-base-german-dbmdz-cased-config.json) • [`pytorch_model.bin`](https://s3.amazonaws.com/models.huggingface.co/bert/bert-base-german-dbmdz-cased-pytorch_model.bin) • [`vocab.txt`](https://s3.amazonaws.com/models.huggingface.co/bert/bert-base-german-dbmdz-cased-vocab.txt)
  | `bert-base-german-dbmdz-uncased` | [`config.json`](https://s3.amazonaws.com/models.huggingface.co/bert/bert-base-german-dbmdz-uncased-config.json) • [`pytorch_model.bin`](https://s3.amazonaws.com/models.huggingface.co/bert/bert-base-german-dbmdz-uncased-pytorch_model.bin) • [`vocab.txt`](https://s3.amazonaws.com/models.huggingface.co/bert/bert-base-german-dbmdz-uncased-vocab.txt)
  
  ## Usage
  
  With Transformers >= 2.3 our German BERT models can be loaded like:
  
  ```python
  from transformers import AutoModel, AutoTokenizer
  
  tokenizer = AutoTokenizer.from_pretrained("dbmdz/bert-base-german-cased")
  model = AutoModel.from_pretrained("dbmdz/bert-base-german-cased")
  ```
  
  ## Results
  
  For results on downstream tasks like NER or PoS tagging, please refer to
  [this repository](https://github.com/stefan-it/fine-tuned-berts-seq).
  
  # 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 🤗
  