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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b0cf178c02a38e815d51347a5bc6fd493e8571281a7766832096d4b05fcf5aad
- Size of remote file:
- 268 MB
- SHA256:
- 76dfad7992093e486f9cdbaffd918d66928d621f34ee9ae5d769e704df19e8f1
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