Instructions to use textattack/facebook-bart-large-MNLI with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use textattack/facebook-bart-large-MNLI with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="textattack/facebook-bart-large-MNLI")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("textattack/facebook-bart-large-MNLI") model = AutoModelForSequenceClassification.from_pretrained("textattack/facebook-bart-large-MNLI", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7ebee69ea5dfd6b8130d9f43651aa490d5260e6c38fe54d9c5364bfa220d69f7
- Size of remote file:
- 1.05 kB
- SHA256:
- 37e79e3d8ae18af3e31e1fb4cc3d12890931cca874af1ff456b3187def909bdd
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