Update app.py

app.py

@@ -42,19 +42,19 @@ tokenizer = AutoTokenizer.from_pretrained(model_id)
 pipe = pipeline(task="text-classification", model=model, tokenizer=tokenizer)
 
 def classify_text(text):
-    start_time = time.time()
+    # start_time = time.time()
     
-    # Get results with all scores returned
+
     results = pipe(text, return_all_scores=True)
     
-    end_time = time.time()
+    # end_time = time.time()
 
     output = f"Sentence: {text}\n"
     
-    # Sort results by score in descending order
+
     sorted_results = sorted(results[0], key=lambda x: x['score'], reverse=True)
     
-    # Print the top 3 highest-scoring labels and scores
+
     for i, result in enumerate(sorted_results[:3]):  # Limiting to the top 3 results
         output += f"Label {i+1}: {result['label']}, Score: {result['score']:.4f}\n"
     
@@ -62,7 +62,7 @@ def classify_text(text):
     
     return output
 
-# Gradio Interface
+
 gr.Interface(
     fn=classify_text,
     title="Sentiment Classifier",