app.py

import streamlit as st
from transformers import AutoTokenizer, AutoModelForCausalLM

# Load the pre-trained model and tokenizer
model_name = "facebook/opt-125m"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name)

# Create the Streamlit app
st.title("Text Summarization App")
text_input = st.text_area("Enter text to summarize")
if st.button("Summarize"):
    input_ids = tokenizer.encode(text_input, return_tensors="pt")
    summary_ids = model.generate(input_ids, max_length=100, min_length=20, do_sample=False)
    summary = tokenizer.decode(summary_ids[0], skip_special_tokens=True)
    st.write("Summary:", summary)