Update app.py

app.py

@@ -1,33 +1,26 @@
 from transformers import pipeline
 import gradio as gr
 
-classifier = pipeline("text-classification", model="bhadresh-savani/bert-base-uncased-emotion")
-
-label_map = {
-    "LABEL_0": "HAM (Not Spam)",
-    "LABEL_1": "SPAM"
-}
+classifier = pipeline(
+    "text-classification",
+    model="mariagrandury/roberta-base-finetuned-sms-spam-detection"
+)
 
 def predict_spam(text):
     result = classifier(text)[0]
-    label = label_map.get(result['label'], "Unknown")
+    label = "SPAM" if result['label'].lower() == "spam" else "HAM (Not Spam)"
     confidence = round(result['score'] * 100, 2)
-    return f" Prediction: {label}\n Confidence: {confidence}%"
+    return f"Prediction: {label}\nConfidence: {confidence}%"
 
-# Build Gradio UI
 gr.Interface(
     fn=predict_spam,
-    inputs=gr.Textbox(lines=4, placeholder="Enter a message..."),
+    inputs=gr.Textbox(lines=4, placeholder="Enter your message..."),
     outputs="text",
-    title=" Spam Detector",
-    description="Detects SPAM vs HAM using a pretrained BERT-tiny model.",
+    title="Spam Detector",
+    description="Detects whether a message is SPAM or not using a fine-tuned RoBERTa model.",
     examples=[
-        "Win a free iPhone now!",
-        "Hey, are we still on for dinner tonight?",
-        "Your OTP is 456123.",
-        "Click here to claim your reward."
+        "Congratulations! You won a prize.",
+        "Hi, are we meeting tomorrow?",
+        "Click to claim your free iPhone!"
     ]
 ).launch()
-
-
-