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:
- ebb7542e540b97aaf8f99ea250dd7cfec102af5ae05edca5eb96bb3ee39606e9
- Size of remote file:
- 1.63 GB
- SHA256:
- 2c51e7702f4ebeef99c85d723acf27a4016e4eb95362e80de290c02ee08d99c8
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