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@@ -112,7 +112,7 @@ As you can see, this is already more complex than the DDPM pipeline which only c
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<Tip>
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💡 Read the [How does Stable Diffusion work?](https://huggingface.co/blog/stable_diffusion#how-does-stable-diffusion-work) blog for more details about how the VAE, UNet, and text encoder models.
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💡 Read the [How does Stable Diffusion work?](https://huggingface.co/blog/stable_diffusion#how-does-stable-diffusion-work) blog for more details about how the VAE, UNet, and text encoder models work.
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</Tip>
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@@ -214,7 +214,7 @@ Next, generate some initial random noise as a starting point for the diffusion p
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```py
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>>> latents = torch.randn(
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... (batch_size, unet.in_channels, height // 8, width // 8),
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... (batch_size, unet.config.in_channels, height // 8, width // 8),
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... generator=generator,
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... )
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>>> latents = latents.to(torch_device)
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