Update app.py

app.py

@@ -1,32 +1,22 @@
-from diffusers import StableDiffusionPipeline, StableDiffusionImg2ImgPipeline, DPMSolverMultistepScheduler
+from diffusers import StableDiffusionPipeline, StableDiffusionImg2ImgPipeline, UniPCMultistepScheduler
 import gradio as gr
 import torch
 from PIL import Image
 
 model_id = 'Norod78/sd2-simpsons-blip'
 prefix = None
-     
-scheduler = DPMSolverMultistepScheduler(
-    beta_start=0.00085,
-    beta_end=0.012,
-    beta_schedule="scaled_linear",
-    num_train_timesteps=1000,
-    trained_betas=None,
-    thresholding=False,
-    algorithm_type="dpmsolver++",
-    solver_type="midpoint",
-    lower_order_final=True,
-)
 
 pipe = StableDiffusionPipeline.from_pretrained(
   model_id,
-  torch_dtype=torch.float16 if torch.cuda.is_available() else torch.float32,
-  scheduler=scheduler)
+  torch_dtype=torch.float16 if torch.cuda.is_available() else torch.float32)
+
+pipe.scheduler = UniPCMultistepScheduler.from_config(pipe.scheduler.config)
 
 pipe_i2i = StableDiffusionImg2ImgPipeline.from_pretrained(
   model_id,
-  torch_dtype=torch.float16 if torch.cuda.is_available() else torch.float32,
-  scheduler=scheduler)
+  torch_dtype=torch.float16 if torch.cuda.is_available() else torch.float32)
+
+pipe_i2i.scheduler = UniPCMultistepScheduler.from_config(pipe_i2i.scheduler.config)
 
 if torch.cuda.is_available():
   pipe = pipe.to("cuda")