Update app.py

app.py

@@ -104,9 +104,11 @@ original_sr_load_model = models.sd2_sr.load_model
 def patched_sr_load_model(*args, **kwargs):
     kwargs['device'] = 'cpu'
     model = original_sr_load_model(*args, **kwargs)
-    # Check if the model has a to method before calling it
-    if hasattr(model, 'to'):
-        model.to('cpu')
+    # Handle DDIM object which doesn't have to() method
+    if hasattr(model, 'model'):  # If there's a main model component
+        model.model.to('cpu')
+    if hasattr(model, 'diffusion'):  # Some diffusion models have this
+        model.diffusion.to('cpu')
     return model
 models.sd2_sr.load_model = patched_sr_load_model
 
@@ -114,10 +116,13 @@ original_sam_load_model = models.sam.load_model
 def patched_sam_load_model(*args, **kwargs):
     kwargs['device'] = 'cpu'
     model = original_sam_load_model(*args, **kwargs)
-    model.to('cpu')
+    # SAM predictor doesn't have to() method but its model does
+    if hasattr(model, 'model'):
+        model.model.to('cpu')
     return model
 models.sam.load_model = patched_sam_load_model
 
+# Load models with CPU
 sr_model = models.sd2_sr.load_model(device='cpu')
 sam_predictor = models.sam.load_model(device='cpu')
 
@@ -125,7 +130,6 @@ inp_model_name = list(inpainting_models.keys())[0]
 inp_model = models.load_inpainting_model(
     inpainting_models[inp_model_name], device='cpu', cache=True)
 
-
 def set_model_from_name(new_inp_model_name):
     global inp_model
     global inp_model_name