Update app.py

app.py

@@ -3,7 +3,7 @@ import numpy as np
 import random
 
 import spaces
-from diffusers import DiffusionPipeline
+from diffusers import DiffusionPipeline, FlowMatchEulerDiscreteScheduler
 import torch
 
 device = "cuda" if torch.cuda.is_available() else "cpu"
@@ -15,6 +15,9 @@ else:
     torch_dtype = torch.float32
 
 pipe = DiffusionPipeline.from_pretrained(model_repo_id, torch_dtype=torch_dtype)
+
+pipe.scheduler = FlowMatchEulerDiscreteScheduler.from_pretrained(model_repo_id, subfolder="scheduler", shift=5)
+
 pipe = pipe.to(device)
 
 MAX_SEED = np.iinfo(np.int32).max