Instructions to use CogComp/bart-faithful-summary-detector with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use CogComp/bart-faithful-summary-detector with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="CogComp/bart-faithful-summary-detector")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("CogComp/bart-faithful-summary-detector") model = AutoModelForSequenceClassification.from_pretrained("CogComp/bart-faithful-summary-detector") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e134f8f180a8642f33b1e0b40896782652fba46894ceb9bb542e98498ee17e0e
- Size of remote file:
- 560 MB
- SHA256:
- b9fa2a12f9cdf80d4bd1404965edbde2ac013eb91d616c79be417abf63ce5697
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