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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from smanjil/German-MedBERT: direct link, hf CLI and curl.
- Browser
- Download file 1.29 kB
-
https://huggingface.co/smanjil/German-MedBERT/resolve/main/training_args.bin
- Command line
-
hf download hf://smanjil/German-MedBERT/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/smanjil/German-MedBERT/resolve/main/training_args.bin
1.29 kB
- Xet hash:
- 66c4206d8fea379d85cb0a83a37134b3ede0369d49f7f6dd0fb58c86869a3dc3
- Size of remote file:
- 1.29 kB
- SHA256:
- 0a06fab865717c3407d58307e6da0a3d676da3e8fcf5755c85ee22690adfbf24
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