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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), [Runway](https://huggingface.co/runwayml), and [Stability AI](https://huggingface.co/stabilityai) Hub organizations!

</Tip>

## 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
