changes

app.py

@@ -12,8 +12,9 @@ config.num_labels = 8  # Set it to the number of classes in your SER task
 
 # Load the pre-trained model with the modified configuration
 model = HubertForSequenceClassification.from_pretrained("superb/hubert-large-superb-er", config=config, ignore_mismatched_sizes=True)
-model.load_state_dict(torch.load(model_name))
 model.to('cuda' if torch.cuda.is_available() else 'cpu')
+model.load_state_dict(torch.load(model_name))
+
 model.eval()
 
 # Load feature extractor