Instructions to use google-bert/bert-base-german-dbmdz-cased with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google-bert/bert-base-german-dbmdz-cased with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="google-bert/bert-base-german-dbmdz-cased")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("google-bert/bert-base-german-dbmdz-cased") model = AutoModelForMaskedLM.from_pretrained("google-bert/bert-base-german-dbmdz-cased") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a53b6b075a4304df113535401ec6e9b0e1a80e4d0bf66c4b9241a485b2cbae2a
- Size of remote file:
- 442 MB
- SHA256:
- c7855bbb476601177dba3d4c69bb5ee07609a3a2ea272c7f5e5116faf4a2a8e2
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