Update app.py

app.py

@@ -14,7 +14,12 @@ if torch.cuda.is_available():
 else:
     torch_dtype = torch.float32
 
-pipe = DiffusionPipeline.from_pretrained(model_repo_id, dtype=torch_dtype, trust_remote_code=True)
+pipe = DiffusionPipeline.from_pretrained(
+    model_repo_id,
+    torch_dtype=torch.float16
+)
+
+pipe.enable_model_cpu_offload()
 pipe = pipe.to(device)
 
 MAX_SEED = np.iinfo(np.int32).max
@@ -36,7 +41,7 @@ def infer(
     if randomize_seed:
         seed = random.randint(0, MAX_SEED)
 
-    generator = torch.Generator().manual_seed(seed)
+    generator = torch.Generator(device=device).manual_seed(seed)
 
     image = pipe(
         prompt=prompt,
@@ -105,7 +110,7 @@ with gr.Blocks(css=css) as demo:
                     minimum=256,
                     maximum=MAX_IMAGE_SIZE,
                     step=32,
-                    value=1024,  # Replace with defaults that work for your model
+                    value=512,  # Replace with defaults that work for your model
                 )
 
                 height = gr.Slider(