app.py

import streamlit as st
import os
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)

import transformers

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(model="EleutherAI/gpt-neo-2.7B")


text = st.text_area("your input")

if text:
    out = generator(text, do_sample=False)
    st.json(out)