# Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("aswinsson/fake_new_classifier")
model = AutoModelForSequenceClassification.from_pretrained("aswinsson/fake_new_classifier")Quick Links
The fake news classifer built using distillbert uncased. Created for the Fatima Fellowship coding challenge and trained on P100 instance for 3 epochs. The model is a binary classifier which predicts 1 in case of real news.
Library: transformers
Language: English
Dataset: https://www.kaggle.com/datasets/clmentbisaillon/fake-and-real-news-dataset
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# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="aswinsson/fake_new_classifier")