Steven Liu
a69754bb87
* start with stable diffusion * fix * finish stable diffusion pipelines * fix path to pipeline output * fix flax paths * fix copies * add up to score sde ve * finish first pass of pipelines * fix copies * second review * align doc titles * more review fixes * final review
37 lines
1.7 KiB
Plaintext
37 lines
1.7 KiB
Plaintext
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# Super-resolution
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The Stable Diffusion upscaler diffusion model was created by the researchers and engineers from [CompVis](https://github.com/CompVis), [Stability AI](https://stability.ai/), and [LAION](https://laion.ai/). It is used to enhance the resolution of input images by a factor of 4.
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<Tip>
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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!
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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!
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</Tip>
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## StableDiffusionUpscalePipeline
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[[autodoc]] StableDiffusionUpscalePipeline
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- all
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- __call__
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- enable_attention_slicing
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- disable_attention_slicing
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- enable_xformers_memory_efficient_attention
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- disable_xformers_memory_efficient_attention
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## StableDiffusionPipelineOutput
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[[autodoc]] pipelines.stable_diffusion.StableDiffusionPipelineOutput |