Instructions to use beatrice-portelli/DiLBERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use beatrice-portelli/DiLBERT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="beatrice-portelli/DiLBERT")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("beatrice-portelli/DiLBERT") model = AutoModelForMaskedLM.from_pretrained("beatrice-portelli/DiLBERT", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9c7f1cc572613f684ec6e41d8877084019619a092e11328cfd2196a26d1e409d
- Size of remote file:
- 438 MB
- SHA256:
- 3d492a1c5a882bf5b2456fa4bc8bb265b18a21fdd1a2bdcffce37f239344d3c6
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