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:
- bdec009fa9dde0931031176fb8bd1e2367d65f0e59e7fb8cc048df909315bf1e
- Size of remote file:
- 1.12 GB
- SHA256:
- 847dd3b004891e595d7791c01019d2983f77384d50c9f6abc227c64e74bb98bf
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