Kaludi/BDA594-fake-news-classification
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How to use Kaludi/BDA594-fake-news-classification with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-classification", model="Kaludi/BDA594-fake-news-classification") # Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("Kaludi/BDA594-fake-news-classification")
model = AutoModelForSequenceClassification.from_pretrained("Kaludi/BDA594-fake-news-classification")This is a Fake News Classifier model that has been trained by Kaludi to determine the authenticity of news articles. It classifies articles into two categories: Real and Fake. By analyzing the content and context of a given article, this model can accurately determine whether the news is genuine or fabricated.
This model supports a Gradio Web UI to run the BDA594-fake-news-classification model: