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| import streamlit as st | |
| from transformers import pipeline | |
| # Initialize the model | |
| model_name = "distilbert-base-uncased-finetuned-sst-2-english" # Example model | |
| classifier = pipeline("text-classification", model=model_name) | |
| # Streamlit app layout | |
| st.title("Intent Classification App") | |
| # Text input | |
| user_input = st.text_input("Enter your text here:") | |
| if user_input: | |
| # Model prediction | |
| result = classifier(user_input) | |
| # Display results | |
| st.write("Intent:", result[0]['label']) | |
| st.write("Confidence:", result[0]['score']) |