Update app.py

app.py

@@ -4,7 +4,7 @@ import soundfile as sf
 from snac import SNAC
 from transformers import AutoTokenizer, AutoModelForCausalLM
 
-device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
+device = torch.device("cpu")  # Changed to CPU mode
 
 def find_last_instance_of_separator(lst, element=50258):
     reversed_list = lst[::-1]
@@ -55,7 +55,7 @@ def reconstruct_tensors(flattened_output):
             tensor2.append(flattened_output[i+5])
             tensor3.append(flattened_output[i+6])
             tensor3.append(flattened_output[i+7])
-            codes = [list_to_torch_tensor(tensor1).to(device), list_to_torch_tensor(tensor2).to(device), list_to_torch_tensor(tensor3).to(device)]
+            codes = [list_to_torch_tensor(tensor1), list_to_torch_tensor(tensor2), list_to_torch_tensor(tensor3)]
 
     if n_tensors == 15:
         for i in range(0, len(flattened_output), 16):
@@ -74,7 +74,7 @@ def reconstruct_tensors(flattened_output):
             tensor3.append(flattened_output[i+13])
             tensor4.append(flattened_output[i+14])
             tensor4.append(flattened_output[i+15])
-            codes = [list_to_torch_tensor(tensor1).to(device), list_to_torch_tensor(tensor2).to(device), list_to_torch_tensor(tensor3).to(device), list_to_torch_tensor(tensor4).to(device)]
+            codes = [list_to_torch_tensor(tensor1), list_to_torch_tensor(tensor2), list_to_torch_tensor(tensor3), list_to_torch_tensor(tensor4)]
 
     return codes
 
@@ -117,4 +117,4 @@ iface = gr.Interface(
 )
 
 if __name__ == "__main__":
-    iface.launch()
+    iface.launch(share=True)