Instructions to use mtreviso/roberta-base-snli with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mtreviso/roberta-base-snli with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="mtreviso/roberta-base-snli")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("mtreviso/roberta-base-snli") model = AutoModelForSequenceClassification.from_pretrained("mtreviso/roberta-base-snli") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ef68de1adb17c5f8eadf383d6745719e6993baaaba084f031729576ca7c79a24
- Size of remote file:
- 499 MB
- SHA256:
- b6c68b95907c765d5b8a5b51a5f8350760f5082543064d2984bff472d8654108
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