Instructions to use smanjil/German-MedBERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use smanjil/German-MedBERT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="smanjil/German-MedBERT")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("smanjil/German-MedBERT") model = AutoModelForMaskedLM.from_pretrained("smanjil/German-MedBERT") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e77a7fbc9a4edb356e0dbeceb67e923a84ed5e62aafdad0f1bfb5607663cf486
- Size of remote file:
- 436 MB
- SHA256:
- d519e7f5455f0094c8251f1488eefb6a1f2e3a6a8e54c43f5fbf40100061d358
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