Update app.py

app.py

@@ -43,12 +43,10 @@ else:
 
 
 # 1. Prepare all the face models
-    face_helper_1, face_helper_2, face_clip_model, face_main_model, eva_transform_mean, eva_transform_std = prepare_face_models(model_path, device, dtype)
+face_helper_1, face_helper_2, face_clip_model, face_main_model, eva_transform_mean, eva_transform_std = prepare_face_models(model_path, device, dtype)
 
 
 # 2. Load Pipeline.
-transformer = ConsisIDTransformer3DModel.from_pretrained_cus(model_path, subfolder=subfolder)
-transformer.to(device, dtype=dtype)
 pipe = ConsisIDPipeline.from_pretrained(model_path, transformer=transformer, torch_dtype=dtype)
 
 # If you're using with lora, add this code
@@ -58,10 +56,6 @@ if lora_path:
 
 
 # 3. Move to device.
-face_helper_1.face_det.to(device)
-face_helper_1.face_parse.to(device)
-face_clip_model.to(device, dtype=dtype)
-transformer.to(device, dtype=dtype)
 pipe.to(device)
 # Save Memory. Turn on if you don't have multiple GPUs or enough GPU memory(such as H100) and it will cost more time in inference, it may also reduce the quality
 pipe.enable_model_cpu_offload()