update app.py

app.py

@@ -27,10 +27,10 @@ flamingo, image_processor, tokenizer, vis_embed_size = create_model_and_transfor
     )
 
 checkpoint_path = hf_hub_download("chendl/mm", "checkpoint_opt350m.pt")
-checkpoint = torch.load(args.checkpoint_path, map_location="cpu")
+checkpoint = torch.load(checkpoint_path, map_location="cpu")
 model_state_dict = {}
-for key in checkpoint["model_state_dict"].keys():
-    model_state_dict[key.replace("module.", "")] = checkpoint["model_state_dict"][key]
+for key in checkpoint.keys():
+    model_state_dict[key.replace("module.", "")] = checkpoint[key]
 if "vision_encoder.logit_scale"in model_state_dict:
     # previous checkpoint has some unnecessary weights
     del model_state_dict["vision_encoder.logit_scale"]