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:
- 9040de3c2b886f6f7ef9bcb8a089e85590a915e9c065be31bc1e9d41d90184c1
- Size of remote file:
- 560 MB
- SHA256:
- e3dba66b36d5c86d8217bb2f62adc39d8eda48761cd3e2716322e80a1d66858f
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