import numpy as np import streamlit as st from transformers import pipeline import torch def bertweet(data): specific_model = pipeline(model="finiteautomata/bertweet-base-sentiment-analysis") result = specific_model(data) label = result[0]['label'] score = result[0]['score'] return label, score def getSent(data, model): if(model == 'Bertweet'): label,score = bertweet(data) col1, col2 = st.columns(2) col1.metric("Feeling",label,None) col2.metric("Score",score,None) def rendPage(): st.title("Sentiment Analysis") userText = st.text_input('User Input', "Hope you are having a great day!") st.text("") type = st.selectbox( 'Choose your model', ('Bertweet','Roberta')) st.text("") if st.button('Calculate'): if(userText!="" and type != None): st.text("") getSent(userText,type) rendPage()