Update app.py

app.py

@@ -81,8 +81,23 @@ def infer(prompt, seed=42, randomize_seed=False, width=1024, height=1024,
         ).sample + init_latents
         
         # Generate final image with adapter disabled
-        # Pass the modulated latents directly to bypass the SCM restriction
         pipe.transformer.disable_adapter_layers()
+        
+        # Manually set timesteps to avoid intermediate_timesteps issue
+        # SCM scheduler only supports intermediate_timesteps when num_inference_steps=2
+        if num_inference_steps == 2:
+            pipe.scheduler.set_timesteps(num_inference_steps, device=device)
+        else:
+            # For num_inference_steps != 2, we need to avoid intermediate_timesteps
+            max_timesteps = 1.57080  # Default from SCM paper
+            pipe.scheduler.set_timesteps(
+                num_inference_steps, 
+                device=device,
+                max_timesteps=max_timesteps,
+                intermediate_timesteps=None
+            )
+        
+        # Now generate the image with pre-set timesteps
         image = pipe(
             latents=modulated_latents,
             prompt_embeds=prompt_embeds,