Instructions to use dbmdz/bert-base-german-uncased with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dbmdz/bert-base-german-uncased with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="dbmdz/bert-base-german-uncased")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("dbmdz/bert-base-german-uncased") model = AutoModelForMaskedLM.from_pretrained("dbmdz/bert-base-german-uncased") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- fb2adc93ec91b0e2b381a485fea32839618f3513a42ee5bdef771c89ed753f7f
- Size of remote file:
- 440 MB
- SHA256:
- da8ca8937ac868ceab520333d582da0a52d76c95d874a131fe1ba6b262f32b97
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