Create app.py

app.py

@@ -0,0 +1,28 @@
+from transformers import pipeline
+
+# Load the pipeline from your Hugging Face model
+pipe = pipeline("text-classification", model="ZachBeesley/Spam-Detector")
+
+# Function to process the input text and return the predicted label
+def predict(text):
+    # Use the pipeline to classify the text
+    result = pipe(text)
+
+    # Extract the predicted label and confidence score
+    label = result[0]["label"]
+    confidence = result[0]["score"]
+
+    # Return the result
+    return f"Predicted label: {label}\nConfidence: {confidence:.2f}"
+
+# Create the Gradio interface
+iface = gr.Interface(
+    fn=predict,
+    inputs=gr.Textbox(label="Email Text", placeholder="Paste your email text here..."),
+    outputs="text",
+    title="Spam Email Detector",
+    description="Enter an email and find out if it's spam or not."
+)
+
+# Launch the interface
+iface.launch()