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:
- 046056b805bdec9e540875291a390b19d4184162818047e20f9ac5a9247206f8
- Size of remote file:
- 1.03 kB
- SHA256:
- 0207791c145232fc098ca14710f5a7427796c82c1b0c6113e9ed1b8c7b7470ba
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