Update app.py

app.py

@@ -88,12 +88,16 @@ def analyze_dna(sequence):
     # Preprocess the input sequence
     inputs = tokenizer(sequence, truncation=True, padding='max_length', max_length=512, return_tensors="pt", return_token_type_ids=False)
 
+    print("tokenization done.")
     # Get model predictions
     _, logits = model(input_ids=inputs['input_ids'], attention_mask=inputs['attention_mask'])
+
+    print("Forward pass done.")
     
     # Convert logits to probabilities
     probabilities = torch.nn.functional.softmax(logits, dim=-1).squeeze().tolist()
-    
+
+    print("Probabilities, done.")
     # Get the top 5 most likely classes
     top_5_indices = sorted(range(len(probabilities)), key=lambda i: probabilities[i], reverse=True)[:5]
     top_5_probs = [probabilities[i] for i in top_5_indices]