add prob level

app.py

@@ -11,19 +11,23 @@ def classify_fake_news(text):
     inputs = tokenizer(text, return_tensors="pt", truncation=True, padding=True)
     outputs = model(**inputs)
     logits = outputs.logits
-    predicted_class = logits.argmax().item()
-    
-    if predicted_class == 1:
-        return "Fake News"
-    else:
-        return "Real News"
+    probs = F.softmax(logits, dim=1) 
+    probs = probs.detach().cpu().numpy()[0]
+
+    labels = ["Real News", "Fake News"]  
+    predicted_class = probs.argmax()
+
+    label = labels[predicted_class]
+    prob = float(probs[predicted_class]) * 100  
+
+    return label, f"{prob:.2f}%"
 
 # Create Gradio interface
 gr.Interface(
     fn=classify_fake_news,
     inputs=gr.Textbox(lines=8, placeholder="Enter text here..."), 
     outputs="text",
-    title="Thai Fake News Classification using mdeberta-v3",
+    title="Thai Fake News Classification using mdeberta-v3-base",
     description="Classifies Thai News as Fake or Real with 91 percent accuracy using a fine-tuned BERT model",
     theme="compact"
 ).launch()