Instructions to use vesteinn/FoBERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use vesteinn/FoBERT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="vesteinn/FoBERT")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("vesteinn/FoBERT") model = AutoModelForMaskedLM.from_pretrained("vesteinn/FoBERT") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 239f90f11c1366663b9e51a55feea2c8a2f33d4596a77a89722c483671b3e7d5
- Size of remote file:
- 498 MB
- SHA256:
- 38603ccddb0a4e4fa8aca1b1bbbc25af14fad161b508558751c28847330e3ac4
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