Update app.py

app.py

@@ -1,17 +1,17 @@
 import streamlit as st
 from transformers import pipeline
-# Load the text classification model pipeline
+
 classifier = pipeline("text-classification", model='isom5240sp24/bert-base-uncased-emotion', return_all_scores=True)
-# Streamlit application title
+
 st.title("Text Classification for you")
 st.write("Classification for 6 emotions: sadness, joy, love, anger, fear, surprise")
-# Text input for user to enter the text to classify
+
 text = st.text_area("Enter the text to classify", "")
-# Perform text classification when the user clicks the "Classify" button
+
+
 if st.button("Classify"):
     results = classifier(text)[0]
-# Perform text classification on the input text results = classifier(text)[0]
-# Display the classification result
+
     max_score = float('-inf') 
     max_label = ''
 for result in results: