Muhammad-Arham's picture
Create app.py
d1b331f verified
raw
history blame
639 Bytes
import gradio as gr
import pickle
# Load the trained model and vectorizer
model = pickle.load(open('spam_model.pkl', 'rb'))
vectorizer = pickle.load(open('vectorizer.pkl', 'rb'))
def predict_sms(message):
transformed_text = vectorizer.transform([message])
prediction = model.predict(transformed_text)[0]
return "Spam" if prediction == 1 else "Not Spam"
# Gradio Web Interface
iface = gr.Interface(
fn=predict_sms,
inputs=gr.Textbox(label="Enter SMS Message"),
outputs=gr.Label(),
title="SMS Spam Classifier",
description="Enter a message to check if it's spam or not."
)
# Launch the app
iface.launch()