app.py

import streamlit as st
from transformers import pipeline

# Load the Hugging Face pipeline
nlp_pipeline = pipeline("text-generation", model="gpt2")

# Streamlit app title and description
st.title("Hugging Face Streamlit Demo")
st.write("This app demonstrates how to use Hugging Face's models with Streamlit.")

# User input for text generation
user_input = st.text_input("Enter some text:", "")

# Generate text using the Hugging Face model
if user_input:
    generated_text = nlp_pipeline(user_input, max_length=50, num_return_sequences=1)
    st.write("Generated Text:")
    st.write(generated_text[0]['generated_text'])