Create app.py

app.py

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+import gradio as gr
+from transformers import pipeline
+
+# Load fake news classifier
+classifier = pipeline("text-classification", model="mrm8488/bert-tiny-finetuned-fake-news", return_all_scores=True)
+
+def detect_fake_news(text):
+    results = classifier(text)[0]
+    results = sorted(results, key=lambda x: x['score'], reverse=True)
+
+    label = results[0]['label']
+    confidence = results[0]['score']
+
+    explanation = f"This article is classified as **{label.upper()}** with a confidence of **{confidence*100:.2f}%**.\n\n"
+    explanation += "### Full Scores:\n"
+    for r in results:
+        explanation += f"- {r['label']}: {r['score']*100:.2f}%\n"
+    
+    return explanation
+
+# Gradio Interface
+demo = gr.Interface(
+    fn=detect_fake_news,
+    inputs=gr.Textbox(lines=12, placeholder="Paste your news article here...", label="📰 News Article"),
+    outputs=gr.Markdown(label="🧠 Fake News Analysis"),
+    title="🕵️‍♀️ Fake News Detector",
+    description="Paste a news article. This app will classify it as FAKE or REAL using a BERT-based model."
+)
+
+demo.launch()