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app.py

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+from transformers import pipeline
+import gradio as gr
+
+# Load spam detection model pipeline
+classifier = pipeline("text-classification", model="mrm8488/bert-tiny-finetuned-sms-spam-detection")
+
+# Define the prediction function
+def predict_spam(text):
+    result = classifier(text)[0]
+    label = result['label']
+    confidence = round(result['score'] * 100, 2)
+    return f"Prediction: {label}\nConfidence: {confidence}%"
+
+# Gradio interface
+gr.Interface(
+    fn=predict_spam,
+    inputs=gr.Textbox(lines=4, placeholder="Enter a message..."),
+    outputs="text",
+    title="Spam Detector",
+    description="Enter a message to check if it's spam or not using a pretrained BERT model.",
+    examples=["Win a free iPhone now!", "Hey, are we still on for dinner tonight?"]
+).launch()

requirements.txt

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+transformers
+gradio
+torch