diff --git a/ldm/models/diffusion/ddim.py b/ldm/models/diffusion/ddim.py
index fb31215db5..d628a87ffa 100644
--- a/ldm/models/diffusion/ddim.py
+++ b/ldm/models/diffusion/ddim.py
@@ -18,8 +18,10 @@ def __init__(self, model, schedule="linear", **kwargs):
 
     def register_buffer(self, name, attr):
         if type(attr) == torch.Tensor:
-            if attr.device != torch.device("cuda"):
-                attr = attr.to(torch.device("cuda"))
+            # if attr.device != torch.device("cuda"):
+            #     attr = attr.to(torch.device("cuda"))
+            if attr.device != torch.device("mps"):
+                attr = attr.to(torch.float32).to(torch.device("mps")).contiguous()
         setattr(self, name, attr)
 
     def make_schedule(self, ddim_num_steps, ddim_discretize="uniform", ddim_eta=0., verbose=True):
diff --git a/scripts/img2img.py b/scripts/img2img.py
index 421e2151d9..e136a715ca 100644
--- a/scripts/img2img.py
+++ b/scripts/img2img.py
@@ -40,7 +40,8 @@ def load_model_from_config(config, ckpt, verbose=False):
         print("unexpected keys:")
         print(u)
 
-    model.cuda()
+    # model.cuda()
+    model.to("mps")
     model.eval()
     return model
 
@@ -199,7 +200,8 @@ def main():
     config = OmegaConf.load(f"{opt.config}")
     model = load_model_from_config(config, f"{opt.ckpt}")
 
-    device = torch.device("cuda") if torch.cuda.is_available() else torch.device("cpu")
+    # device = torch.device("cuda") if torch.cuda.is_available() else torch.device("cpu")
+    device = torch.device("mps") if torch.backends.mps.is_available() else torch.device("cpu")
     model = model.to(device)
 
     if opt.plms:
@@ -242,7 +244,8 @@ def main():
 
     precision_scope = autocast if opt.precision == "autocast" else nullcontext
     with torch.no_grad():
-        with precision_scope("cuda"):
+        # with precision_scope("cuda"):
+        with nullcontext("mps"):
             with model.ema_scope():
                 tic = time.time()
                 all_samples = list()