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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3734102adf367275550008d0ea5d65e1678370ecc70b6e3c1e9445088539abb8
- Size of remote file:
- 623 Bytes
- SHA256:
- b7e0189f63e54dfab03937ea72158839b1c69101258a3d6704f3be974933751e
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