Instructions to use dbmdz/bert-base-italian-uncased with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dbmdz/bert-base-italian-uncased with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="dbmdz/bert-base-italian-uncased")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("dbmdz/bert-base-italian-uncased") model = AutoModelForMaskedLM.from_pretrained("dbmdz/bert-base-italian-uncased") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2de3d5963e60a0e5115b7e94ed2390e523d4213e19527ac564f388b2f2084139
- Size of remote file:
- 440 MB
- SHA256:
- 8e84a77c85d828cc87fd07f952be6488119c0aaf04afadd4041155749f1e4adc
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