app.py

import streamlit as st
from transformers import GPT2LMHeadModel, GPT2Tokenizer

# Load the GPT-2 model and tokenizer
model_name = 'gpt2-large'
model = GPT2LMHeadModel.from_pretrained(model_name)
tokenizer = GPT2Tokenizer.from_pretrained(model_name)

st.title("Article Generator")

# Input for the article title
title = st.text_input("Enter the title of the article")

# Generate the article
if st.button("Generate Article"):
    if title:
        input_ids = tokenizer.encode(title, return_tensors='pt')
        output = model.generate(input_ids, max_length=500, num_return_sequences=1, no_repeat_ngram_size=2, early_stopping=True)
        article = tokenizer.decode(output[0], skip_special_tokens=True)
        st.write(article)
    else:
        st.warning("Please enter a title to generate an article")