app.py

import streamlit as st
from transformers import pipeline
import gc

st.header("Sentiment-demo-app")
st.subheader("Please be patient and wait up to a minute until the demo app is loaded.")
st.caption("This is a very simple demo application for a zero-shot classification pipeline to classify positive, neutral, or negative sentiment for a short text. Enter your text in the box below and press CTRl+ENTER to run the model.")

pipe = pipeline("text-classification", model='tabularisai/multilingual-sentiment-analysis') #"zero-shot-classification" model='facebook/bart-large-mnli')

text = st.text_area('Enter text here!')
#candidate_labels = ['Positive', 'Neutral', 'Negative']
result = pipe(texts)

if text:
  out = pipe(text, result)
  st.json(out)
  del out
  gc.collect()