app.py

import streamlit as st
from transformers import pipeline

# Load your model; this example uses the GPT-2 model for text generation.
generator = pipeline('text-generation', model='gpt2')

st.title('Hugging Face Model Integration')

# Text input
user_input = st.text_input("Type a sentence to complete", "Streamlit is ")

# Generate text button
if st.button('Generate'):
    # Generate text
    result = generator(user_input, max_length=50, num_return_sequences=1)
    # Display the generated text
    st.text_area("Generated Text", result[0]['generated_text'], height=150)