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autoencoder_tiny.md

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Tiny AutoEncoder

Tiny AutoEncoder for Stable Diffusion (TAESD) was introduced in madebyollin/taesd by Ollin Boer Bohan. It is a tiny distilled version of Stable Diffusion's VAE that can quickly decode the latents in a [StableDiffusionPipeline] or [StableDiffusionXLPipeline] almost instantly.

To use with Stable Diffusion v-2.1:

importtorchfromdiffusersimportDiffusionPipeline, AutoencoderTinypipe=DiffusionPipeline.from_pretrained( "stabilityai/stable-diffusion-2-1-base", torch_dtype=torch.float16 ) pipe.vae=AutoencoderTiny.from_pretrained("madebyollin/taesd", torch_dtype=torch.float16) pipe=pipe.to("cuda") prompt="slice of delicious New York-style berry cheesecake"image=pipe(prompt, num_inference_steps=25).images[0] image

To use with Stable Diffusion XL 1.0

importtorchfromdiffusersimportDiffusionPipeline, AutoencoderTinypipe=DiffusionPipeline.from_pretrained( "stabilityai/stable-diffusion-xl-base-1.0", torch_dtype=torch.float16 ) pipe.vae=AutoencoderTiny.from_pretrained("madebyollin/taesdxl", torch_dtype=torch.float16) pipe=pipe.to("cuda") prompt="slice of delicious New York-style berry cheesecake"image=pipe(prompt, num_inference_steps=25).images[0] image

AutoencoderTiny

[[autodoc]] AutoencoderTiny

AutoencoderTinyOutput

[[autodoc]] models.autoencoders.autoencoder_tiny.AutoencoderTinyOutput

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