Instructions to use ZurichNLP/swissbert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ZurichNLP/swissbert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="ZurichNLP/swissbert")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("ZurichNLP/swissbert") model = AutoModelForMaskedLM.from_pretrained("ZurichNLP/swissbert", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ee1bba7cffd828054f5f8c04d0c5df0ec398d998afdad9e86feeae3a1d72f675
- Size of remote file:
- 641 MB
- SHA256:
- 3621abd43ac00e35367a180626eccb4091493178ed6f922fc78717e2a4c06fed
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