app.py

import streamlit as st
from transformers import AutoTokenizer, AutoModelForCausalLM
import torch

tokenizer = AutoTokenizer.from_pretrained("ahmadmac/Pretrained-GPT2")
model = AutoModelForCausalLM.from_pretrained("ahmadmac/Pretrained-GPT2")

def generate_text(prompt, max_length=50, num_return_sequences=1, temperature=0.7):
  input_ids = tokenizer(prompt, return_tensors="pt").input_ids
  output = model.generate(
      input_ids,
      max_length=max_length,
      num_return_sequences=num_return_sequences,
      temperature=0.7  

  )
  return tokenizer.decode(output[0], skip_special_tokens=True)

def main():
  st.title("Text Generator")
  prompt = st.text_input("Enter your prompt:")
  if st.button("Generate"):
    generated_text = generate_text(prompt)
    st.text_area("Generated Text:", generated_text)

if __name__ == "__main__":
  main()