Instructions to use dicta-il/dictabert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dicta-il/dictabert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="dicta-il/dictabert")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("dicta-il/dictabert") model = AutoModelForMaskedLM.from_pretrained("dicta-il/dictabert") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 45e9b031e336052b4d1a205d35e461f5c8a4cddcd4d7db22802f68686a076617
- Size of remote file:
- 738 MB
- SHA256:
- 5c1f3f5a922bcf801d11cac04332cc167377355a5be07a73cfde680864927b70
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