diff --git a/src/diffusers/schedulers/scheduling_dpmsolver_singlestep.py b/src/diffusers/schedulers/scheduling_dpmsolver_singlestep.py
index 3329919cfb02..6841a34a6489 100644
--- a/src/diffusers/schedulers/scheduling_dpmsolver_singlestep.py
+++ b/src/diffusers/schedulers/scheduling_dpmsolver_singlestep.py
@@ -330,6 +330,7 @@ def set_timesteps(
             # Clipping the minimum of all lambda(t) for numerical stability.
             # This is critical for cosine (squaredcos_cap_v2) noise schedule.
             clipped_idx = torch.searchsorted(torch.flip(self.lambda_t, [0]), self.config.lambda_min_clipped)
+            clipped_idx = clipped_idx.item()
             timesteps = (
                 np.linspace(0, self.config.num_train_timesteps - 1 - clipped_idx, num_inference_steps + 1)
                 .round()[::-1][:-1]