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# Latent upscaler

The Stable Diffusion latent upscaler model was created by [Katherine Crowson](https://github.com/crowsonkb/k-diffusion) in collaboration with [Stability AI](https://stability.ai/). It is used to enhance the output image resolution by a factor of 2 (see this demo [notebook](https://colab.research.google.com/drive/1o1qYJcFeywzCIdkfKJy7cTpgZTCM2EI4) for a demonstration of the original implementation).

> [!TIP]
> Make sure to check out the Stable Diffusion [Tips](overview#tips) section to learn how to explore the tradeoff between scheduler speed and quality, and how to reuse pipeline components efficiently!
>
> If you're interested in using one of the official checkpoints for a task, explore the [CompVis](https://huggingface.co/CompVis) and [Stability AI](https://huggingface.co/stabilityai) Hub organizations!

## StableDiffusionLatentUpscalePipeline

[[autodoc]] StableDiffusionLatentUpscalePipeline
	- all
	- __call__
	- enable_sequential_cpu_offload
	- enable_attention_slicing
	- disable_attention_slicing
	- enable_xformers_memory_efficient_attention
	- disable_xformers_memory_efficient_attention

## StableDiffusionPipelineOutput

[[autodoc]] pipelines.stable_diffusion.StableDiffusionPipelineOutput