Instructions to use textattack/roberta-base-QNLI with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use textattack/roberta-base-QNLI with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="textattack/roberta-base-QNLI")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("textattack/roberta-base-QNLI") model = AutoModelForSequenceClassification.from_pretrained("textattack/roberta-base-QNLI") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c5b6a83b5f96f1f96fd7e42bc2bc1f8840e7bd56abd5e205cb91db7d2755449c
- Size of remote file:
- 499 MB
- SHA256:
- 64f1d1d41f95a1220fe144ea396388fe0399413ebda50a59c0d1f4d9b627cffc
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