diff --git a/src/diffusers/pipelines/semantic_stable_diffusion/pipeline_semantic_stable_diffusion.py b/src/diffusers/pipelines/semantic_stable_diffusion/pipeline_semantic_stable_diffusion.py
index 29082beb9128..ce7e804dde63 100644
--- a/src/diffusers/pipelines/semantic_stable_diffusion/pipeline_semantic_stable_diffusion.py
+++ b/src/diffusers/pipelines/semantic_stable_diffusion/pipeline_semantic_stable_diffusion.py
@@ -442,7 +442,7 @@ def __call__(
         if do_classifier_free_guidance:
             uncond_tokens: List[str]
             if negative_prompt is None:
-                uncond_tokens = [""]
+                uncond_tokens = [""] * batch_size
             elif type(prompt) is not type(negative_prompt):
                 raise TypeError(
                     f"`negative_prompt` should be the same type to `prompt`, but got {type(negative_prompt)} !="
@@ -471,7 +471,7 @@ def __call__(
 
             # duplicate unconditional embeddings for each generation per prompt, using mps friendly method
             seq_len = uncond_embeddings.shape[1]
-            uncond_embeddings = uncond_embeddings.repeat(batch_size, num_images_per_prompt, 1)
+            uncond_embeddings = uncond_embeddings.repeat(1, num_images_per_prompt, 1)
             uncond_embeddings = uncond_embeddings.view(batch_size * num_images_per_prompt, seq_len, -1)
 
             # For classifier free guidance, we need to do two forward passes.