app.py

import streamlit as st
import transformers
import numpy as np

# Load the pre-trained model
model = transformers.pipeline("text2text-generation", model="mrm8488/t5-base-finetuned-topic-modeling")

# Define the Streamlit app
def main():
    st.title("Topic Modeling with Hugging Face")
    text = st.text_area("Enter some text to generate topics", height=200)

    if st.button("Generate Topics"):
        # Generate topics
        topics = model(text, max_length=50, do_sample=True, num_beams=5, temperature=0.7)

        # Print topics
        st.write("Top 5 topics:")
        for i in range(5):
            st.write(f"{i+1}. {topics[i]['generated_text']}")

if __name__ == "__main__":
    main()