app.py

from transformers import pipeline
import streamlit as st

@st.cache
sentiment = pipeline(
  "sentiment-analysis",
    model="avichr/heBERT_sentiment_analysis",
)
st.title("Find sentiment")
st.write("HebEMO is a tool to detect polarity and extract emotions from Hebrew user-generated content (UGC), which was trained on a unique Covid-19 related dataset that we collected and annotated. HebEMO yielded a high performance of weighted average F1-score = 0.96 for polarity classification. Emotion detection reached an F1-score of 0.78-0.97, with the exception of *surprise*, which the model failed to capture (F1 = 0.41). These results are better than the best-reported performance, even when compared to the English language.")
sent = st.text_area("Text", default_value, height = 20)
st.write (sentiment(sent))