Update app.py

app.py

@@ -2,12 +2,15 @@ import streamlit as st
 from transformers import pipeline
 
 # Create a Streamlit app
-st.title("BERT Text Classification : sentiment analysis")
+st.title("Text Classification with Hugginface: sentiment analysis case")
 
 # Get user input
 text = st.text_input("Enter some text to classify:")
 
-classifier = pipeline("sentiment-analysis", model="distilbert-base-uncased-finetuned-sst-2-english")
+#pipeline for sentiment analysis
+sentiment = pipeline("sentiment-analysis", model="distilbert-base-uncased-finetuned-sst-2-english")
 
-if st.button('Click me'):
-    st.write(classifier(text)[0]['label'],' avec un score ', classifier(text)[0]['score'])
+#Print the sentiment and the corresponding score when the button is clicked
+if st.button('Click to get the sentiment'):
+    output = sentiment(text)
+    st.write(output[0]['label'],' avec un score ', output[0]['score'])