Update app.py

app.py

@@ -135,7 +135,7 @@ def main():
     if ptuning_checkpoint is not None:
         print(f"Loading prefix_encoder weight from {ptuning_checkpoint}")
         model = AutoModel.from_pretrained("THUDM/chatglm-6b-int4", config=config, trust_remote_code=True)
-        prefix_state_dict = torch.load(os.path.join(ptuning_checkpoint, "pytorch_model.bin"))
+        prefix_state_dict = torch.load(os.path.join(ptuning_checkpoint, "pytorch_model.bin"), map_location='cpu')
         new_prefix_state_dict = {}
         for k, v in prefix_state_dict.items():
             if k.startswith("transformer.prefix_encoder."):