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))