Update app.py

app.py

@@ -3,22 +3,25 @@ from transformers import pipeline
 
 # Load the text classification model pipeline
 classifier = pipeline("text-classification", model="lqqqqqqqqq/FinetunedModelGr9", return_all_scores=True)
+
 # Streamlit application title
 st.title("Text Classification")
 st.write("Classification for 3 labels: negative, neutual, positive")
+
 # 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"):
-# 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:
-if result['score'] > max_score:
-max_score = result['score']
-max_label = result['label']
-st.write("Text:", text)
-st.write("Label:", max_label)
-st.write("Score:", max_score)
+    # 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:
+    if result['score'] > max_score:
+        max_score = result['score']
+        max_label = result['label']
+    st.write("Text:", text)
+    st.write("Label:", max_label)
+    st.write("Score:", max_score)