Instructions to use ModelTC/bart-base-mnli with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ModelTC/bart-base-mnli with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ModelTC/bart-base-mnli")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ModelTC/bart-base-mnli") model = AutoModelForSequenceClassification.from_pretrained("ModelTC/bart-base-mnli") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b87758a522ea856574db036fd5fcaeef14d076fdfa9116177e1254db8e530596
- Size of remote file:
- 2.99 kB
- SHA256:
- c063beffa5629baa9fe8e38412f704068d6a4c30a34c5cc70d4866f81fac8eb5
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