Instructions to use ModelTC/bart-base-cola with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ModelTC/bart-base-cola with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ModelTC/bart-base-cola")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ModelTC/bart-base-cola") model = AutoModelForSequenceClassification.from_pretrained("ModelTC/bart-base-cola") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 13a7018dbd4f60411e71d318b06fca8d8a9f892ad5a9abc6918a1fa23fb8136a
- Size of remote file:
- 560 MB
- SHA256:
- a85bb0f3b54c44af4b79a488efde4248a095de99fbe08d638d992b9af06f627b
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