# Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("Gaborandi/Bert_news_classifier")
model = AutoModelForSequenceClassification.from_pretrained("Gaborandi/Bert_news_classifier")Quick Links
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Check out the documentation for more information.
- Fine-tuned BERT model on news data
- the model used this data: https://www.kaggle.com/datasets/sadikaljarif/fake-news-detection-dataset-english
- the model achieved AUC score = 0.9990 with just 3 epochs
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# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Gaborandi/Bert_news_classifier")