Instructions to use DraiP/Fake_News_Classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use DraiP/Fake_News_Classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="DraiP/Fake_News_Classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("DraiP/Fake_News_Classifier") model = AutoModelForSequenceClassification.from_pretrained("DraiP/Fake_News_Classifier") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2889428d291b62684ff0b8c7ccb73bcd5400c9892af11f3f29050ba9ed491922
- Size of remote file:
- 268 MB
- SHA256:
- a52efd2d158e8a4a7e4513a042ab7d290e53802ca7a99b43696b92e849f5c34e
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