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Update app.py
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import gradio as gr
from transformers import pipeline
# Use a valid public model
classifier = pipeline("text-classification", model="michiyasunaga/BERT-fake-news-detection")
def detect_fake_news(text):
result = classifier(text)[0]
label = result['label']
score = result['score']
explanation = (
f"The model predicts this news is **{label}** "
f"with a confidence of **{score:.2f}**.\n\n"
"🧠 This is based on BERT fine-tuned on a fake news dataset."
)
return explanation
demo = gr.Interface(fn=detect_fake_news,
inputs=gr.Textbox(lines=10, placeholder="Paste your news article here..."),
outputs="markdown",
title="🕵️ Fake News Detector",
description="An NLP app that predicts whether a news article is fake or real using BERT.")
demo.launch()