diff --git a/src/diffusers/schedulers/scheduling_ddim.py b/src/diffusers/schedulers/scheduling_ddim.py
index 33d9bafb8aed..a1022678b3c7 100644
--- a/src/diffusers/schedulers/scheduling_ddim.py
+++ b/src/diffusers/schedulers/scheduling_ddim.py
@@ -157,7 +157,7 @@ def __init__(
 
         # setable values
         self.num_inference_steps = None
-        self.timesteps = torch.from_numpy(np.arange(0, num_train_timesteps)[::-1].copy())
+        self.timesteps = torch.from_numpy(np.arange(0, num_train_timesteps)[::-1].copy().astype(np.int64))
 
     def scale_model_input(self, sample: torch.FloatTensor, timestep: Optional[int] = None) -> torch.FloatTensor:
         """
@@ -200,7 +200,7 @@ def set_timesteps(self, num_inference_steps: int, device: Union[str, torch.devic
         step_ratio = self.config.num_train_timesteps // self.num_inference_steps
         # creates integer timesteps by multiplying by ratio
         # casting to int to avoid issues when num_inference_step is power of 3
-        timesteps = (np.arange(0, num_inference_steps) * step_ratio).round()[::-1].copy()
+        timesteps = (np.arange(0, num_inference_steps) * step_ratio).round()[::-1].copy().astype(np.int64)
         self.timesteps = torch.from_numpy(timesteps).to(device)
         self.timesteps += offset