Instructions to use dbmdz/bert-base-italian-cased with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dbmdz/bert-base-italian-cased with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="dbmdz/bert-base-italian-cased")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("dbmdz/bert-base-italian-cased") model = AutoModelForMaskedLM.from_pretrained("dbmdz/bert-base-italian-cased") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d1a4fbe733baf0df9e7c665eca489f548d389c727bec57f2c1af291d1e3c31b2
- Size of remote file:
- 440 MB
- SHA256:
- 3d601914bed8ce474ab5bde1ccfc99a545ab5fa808e0fdc8b46afe8404826430
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