Changed to DDPM pipeline

app.py

@@ -1,18 +1,18 @@
 import gradio as gr
 import numpy as np
 import random
-from diffusers import DiffusionPipeline
+from diffusers import DiffusionPipeline, DDPMPipeline, DDPMScheduler
 import torch
 
 device = "cuda" if torch.cuda.is_available() else "cpu"
-
+noise_scheduler = DDPMScheduler(num_train_timesteps=1000)
 if torch.cuda.is_available():
     torch.cuda.max_memory_allocated(device=device)
-    pipe = DiffusionPipeline.from_pretrained("FrozenScar/cartoon_face", torch_dtype=torch.float16, variant="fp16", use_safetensors=True)
+    pipe = DDPMPipeline.from_pretrained("FrozenScar/cartoon_face", torch_dtype=torch.float16, variant="fp16", use_safetensors=True)
     pipe.enable_xformers_memory_efficient_attention()
     pipe = pipe.to(device)
 else: 
-    pipe = DiffusionPipeline.from_pretrained("FrozenScar/cartoon_face", use_safetensors=True)
+    pipe = DDPMPipeline.from_pretrained("FrozenScar/cartoon_face", scheduler=noise_scheduler, use_safetensors=True)
     pipe = pipe.to(device)
 
 MAX_SEED = np.iinfo(np.int32).max