Instructions to use leondz/refutation_detector_distilbert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use leondz/refutation_detector_distilbert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="leondz/refutation_detector_distilbert")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("leondz/refutation_detector_distilbert") model = AutoModelForSequenceClassification.from_pretrained("leondz/refutation_detector_distilbert") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 57db43ecf1719eb4c44211bc47bf709a880e21e4662d7262741121a03cee3bc2
- Size of remote file:
- 268 MB
- SHA256:
- dde87fde2ed505b9db2265b7f82c2341790f2e7750e8f077277312b81ef4e94d
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