Instructions to use textattack/facebook-bart-large-QNLI with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use textattack/facebook-bart-large-QNLI with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="textattack/facebook-bart-large-QNLI")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("textattack/facebook-bart-large-QNLI") model = AutoModelForSequenceClassification.from_pretrained("textattack/facebook-bart-large-QNLI", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 82f469645061ea5330dbf1f84b6553d9853f1073d8e0c227597b5f6e2b73d9d8
- Size of remote file:
- 1.63 GB
- SHA256:
- 27902e7456cd1034b9aebb723da23ac243e71623e69eb8b2b3f213cf827d9962
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