diff --git a/docs/source/en/stable_diffusion.mdx b/docs/source/en/stable_diffusion.mdx
index eebe0ec660f2..0cec07834507 100644
--- a/docs/source/en/stable_diffusion.mdx
+++ b/docs/source/en/stable_diffusion.mdx
@@ -153,7 +153,7 @@ def get_inputs(batch_size=1):
 You'll also need a function that'll display each batch of images:
 
 ```python
-from PIL import image
+from PIL import Image
 
 
 def image_grid(imgs, rows=2, cols=2):
@@ -268,4 +268,4 @@ In this tutorial, you learned how to optimize a [`DiffusionPipeline`] for comput
 
 - Enable [xFormers](./optimization/xformers) memory efficient attention mechanism for faster speed and reduced memory consumption.
 - Learn how in [PyTorch 2.0](./optimization/torch2.0), [`torch.compile`](https://pytorch.org/docs/stable/generated/torch.compile.html) can yield 2-9% faster inference speed.
-- Many optimization techniques for inference are also included in this memory and speed [guide](./optimization/fp16), such as memory offloading.
\ No newline at end of file
+- Many optimization techniques for inference are also included in this memory and speed [guide](./optimization/fp16), such as memory offloading.