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
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# NELA-GT_Classifier
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This model was Fine-Tuned on
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## Model description
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tags:
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- name: Fake_News_Classifier
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results: []
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metrics:
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# NELA-GT_Classifier
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This model was Fine-Tuned on a Fake News dataset.
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## Model description
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