Update with the new API change

app.py

@@ -1,23 +1,23 @@
 import torch
 from diffusers import DDIMPipeline, DDPMPipeline, PNDMPipeline
 from diffusers import DDIMScheduler, DDPMScheduler, PNDMScheduler
-from diffusers import UNetUnconditionalModel
+from diffusers import UNet2DModel
 import gradio as gr
 import PIL.Image
 import numpy as np
 import random
 
 model_id = "google/ddpm-celebahq-256"
-model = UNetUnconditionalModel.from_pretrained(model_id, subfolder="unet")
+model = UNet2DModel.from_pretrained(model_id)
 
 # load model and scheduler
-ddpm_scheduler = DDPMScheduler.from_config(model_id, subfolder="scheduler")
+ddpm_scheduler = DDPMScheduler.from_config(model_id)
 ddpm_pipeline = DDPMPipeline(unet=model, scheduler=ddpm_scheduler)
 
-ddim_scheduler = DDIMScheduler.from_config(model_id, subfolder="scheduler")
+ddim_scheduler = DDIMScheduler.from_config(model_id)
 ddim_pipeline = DDIMPipeline(unet=model, scheduler=ddim_scheduler)
 
-pndm_scheduler = PNDMScheduler.from_config(model_id, subfolder="scheduler")
+pndm_scheduler = PNDMScheduler.from_config(model_id)
 pndm_pipeline = PNDMPipeline(unet=model, scheduler=pndm_scheduler)
 
 # run pipeline in inference (sample random noise and denoise)