Instructions to use mascIT/bert-tiny-ita with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mascIT/bert-tiny-ita with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="mascIT/bert-tiny-ita")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("mascIT/bert-tiny-ita") model = AutoModelForMaskedLM.from_pretrained("mascIT/bert-tiny-ita") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 55e8ff451487c71470866c8d46995336ada66c6049af6f7f011653fbbb1dbe04
- Size of remote file:
- 12.3 MB
- SHA256:
- 56b8d6d08e93e750529be282d9262ee512dd5b2136f6ad1638e311aab262659f
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