Instructions to use Bruck08/Fake-News-Detection-using-PyTloop with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Bruck08/Fake-News-Detection-using-PyTloop with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Bruck08/Fake-News-Detection-using-PyTloop")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Bruck08/Fake-News-Detection-using-PyTloop") model = AutoModelForSequenceClassification.from_pretrained("Bruck08/Fake-News-Detection-using-PyTloop", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 13aca95e569168e63561c91f122089b2aeff958562c242a7d38017ec9364fed5
- Size of remote file:
- 438 MB
- SHA256:
- e2ced056928517116314b88674210e5a3feb413952866073481898c5eda69ece
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