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:
- ed4248c0ffe1927e43ca3d2929006da0c87c254e9509680b667a16363f7a9964
- Size of remote file:
- 501 MB
- SHA256:
- 92f6208a80c0a8e6d2f890aff44903f4d84478d94b898dce53ea6719f1ed3b31
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