app.py

import streamlit as st
from transformers import pipeline

pipe = pipeline('sentiment-analysis')
text = st.text_area('enter some text!')

if text:
    out = pipe(text)
    st.json(out)

# text = st.text_area('enter some text!')

# classifier = pipeline("text-classification", model="hun3359/klue-bert-base-sentiment")
# preds = classifier(text, top_k=None)

# sorted_preds = sorted(preds, key=lambda x: x['score'], reverse=True)

# for item in sorted_preds:
#     item['score'] = round(item['score'], 5)

# if text:
#     st.json(sorted_preds)