feature_extractor = CLIPFeatureExtractor.from_pretrained(pipe_id, subfolder="feature_extractor") In steps 4 and 5, the custom UNet and pipeline implementation must match the format shown in their files for this example to work. Now you’ll load a custom UNet, which in this example, has already been implemented in the showone_unet_3d_condition.py script for your convenience. You’ll notice the UNet3DConditionModel class name is changed to ShowOneUNet3DConditionModel because UNet3DConditionModel already exists in Diffusers. Any components needed for the ShowOneUNet3DConditionModel class should be placed in the showone_unet_3d_condition.py script. Once this is done, you can initialize the UNet:   Copied from showone_unet_3d_condition import ShowOneUNet3DConditionModel