Update app.py

app.py

@@ -1,19 +1,10 @@
 import gradio as gr
 from transformers import pipeline
 
-# Load the text classification model pipeline
 classifier = pipeline("text-classification", model='isom5240ust/bert-base-uncased-emotion', return_all_scores=True)
 
 def classify_text(text):
-    """
-    Classifies the input text and returns the label and score of the most likely emotion.
 
-    Args:
-        text (str): The text to classify.
-
-    Returns:
-        tuple: A tuple containing the label and score of the most likely emotion.
-    """
     results = classifier(text)[0]
 
     max_score = float('-inf')
@@ -29,7 +20,7 @@ def classify_text(text):
 # Gradio interface
 iface = gr.Interface(
     fn=classify_text,
-    inputs=gr.Textbox(lines=3, placeholder="Enter text here..."),
+    inputs=gr.Textbox(placeholder="Enter text here..."),
     outputs=[
         gr.Textbox(label="Label"),
         gr.Textbox(label="Score")