72 lines
3.1 KiB
Markdown
72 lines
3.1 KiB
Markdown
---
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language: german
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license: mit
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---
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# 🤗 + 📚 dbmdz German BERT models
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In this repository the MDZ Digital Library team (dbmdz) at the Bavarian State
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Library open sources another German BERT models 🎉
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# German BERT
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## Stats
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In addition to the recently released [German BERT](https://deepset.ai/german-bert)
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model by [deepset](https://deepset.ai/) we provide another German-language model.
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The source data for the model consists of a recent Wikipedia dump, EU Bookshop corpus,
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Open Subtitles, CommonCrawl, ParaCrawl and News Crawl. This results in a dataset with
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a size of 16GB and 2,350,234,427 tokens.
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For sentence splitting, we use [spacy](https://spacy.io/). Our preprocessing steps
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(sentence piece model for vocab generation) follow those used for training
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[SciBERT](https://github.com/allenai/scibert). The model is trained with an initial
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sequence length of 512 subwords and was performed for 1.5M steps.
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This release includes both cased and uncased models.
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## Model weights
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Currently only PyTorch-[Transformers](https://github.com/huggingface/transformers)
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compatible weights are available. If you need access to TensorFlow checkpoints,
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please raise an issue!
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| Model | Downloads
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| -------------------------------- | ---------------------------------------------------------------------------------------------------------------
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| `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)
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| `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)
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## Usage
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With Transformers >= 2.3 our German BERT models can be loaded like:
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```python
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from transformers import AutoModel, AutoTokenizer
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tokenizer = AutoTokenizer.from_pretrained("dbmdz/bert-base-german-cased")
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model = AutoModel.from_pretrained("dbmdz/bert-base-german-cased")
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```
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## Results
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For results on downstream tasks like NER or PoS tagging, please refer to
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[this repository](https://github.com/stefan-it/fine-tuned-berts-seq).
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# Huggingface model hub
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All 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 BERT models just open an issue
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[here](https://github.com/dbmdz/berts/issues/new) 🤗
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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 🤗
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