diff --git a/modules/processing.py b/modules/processing.py
index ab7b3b7d..9c3673de 100644
--- a/modules/processing.py
+++ b/modules/processing.py
@@ -94,7 +94,7 @@ def txt2img_image_conditioning(sd_model, x, width, height):
     return image_conditioning
 
 
-class StableDiffusionProcessing():
+class StableDiffusionProcessing:
     """
     The first set of paramaters: sd_models -> do_not_reload_embeddings represent the minimum required to create a StableDiffusionProcessing
     """
@@ -102,7 +102,6 @@ class StableDiffusionProcessing():
         if sampler_index is not None:
             print("sampler_index argument for StableDiffusionProcessing does not do anything; use sampler_name", file=sys.stderr)
 
-        self.sd_model = sd_model
         self.outpath_samples: str = outpath_samples
         self.outpath_grids: str = outpath_grids
         self.prompt: str = prompt
@@ -156,6 +155,10 @@ class StableDiffusionProcessing():
         self.all_subseeds = None
         self.iteration = 0
 
+    @property
+    def sd_model(self):
+        return shared.sd_model
+
     def txt2img_image_conditioning(self, x, width=None, height=None):
         self.is_using_inpainting_conditioning = self.sd_model.model.conditioning_key in {'hybrid', 'concat'}
 
@@ -236,7 +239,6 @@ class StableDiffusionProcessing():
         raise NotImplementedError()
 
     def close(self):
-        self.sd_model = None
         self.sampler = None
 
 
@@ -471,7 +473,6 @@ def process_images(p: StableDiffusionProcessing) -> Processed:
 
             if k == 'sd_model_checkpoint':
                 sd_models.reload_model_weights()  # make onchange call for changing SD model
-                p.sd_model = shared.sd_model
 
             if k == 'sd_vae':
                 sd_vae.reload_vae_weights()  # make onchange call for changing VAE
diff --git a/scripts/xy_grid.py b/scripts/xy_grid.py
index bf4ba92f..6629f5d5 100644
--- a/scripts/xy_grid.py
+++ b/scripts/xy_grid.py
@@ -86,7 +86,6 @@ def apply_checkpoint(p, x, xs):
     if info is None:
         raise RuntimeError(f"Unknown checkpoint: {x}")
     modules.sd_models.reload_model_weights(shared.sd_model, info)
-    p.sd_model = shared.sd_model
 
 
 def confirm_checkpoints(p, xs):