app.py

import streamlit as st
import os
import torch  # Add this line to import the torch library
import transformers


HF_TOKEN = os.getenv('HF_TOKEN')
from huggingface_hub import HfFolder
# Set the token using HfFolder (this persists the token)
HfFolder.save_token(HF_TOKEN)

from transformers import pipeline

# Load the model, specifying the use of GPU if available

#device = 0 if torch.cuda.is_available() else -1  # use GPU if available

#generator = pipeline('text-generation', model='EleutherAI/gpt-neo-2.7B', device=device)


generator = pipeline("text-generation", model="gpt-2")


st.title("text class")
st.write("your text.")
text = st.text_area("your input")

if text:
    out = generator(text, do_sample=False)
    st.json(out)
    st.write(f"reply: {out}")