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license: mit |
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--- |
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# 🍰 Tiny AutoEncoder for Stable Diffusion (XL) |
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[TAESDXL](https://github.com/madebyollin/taesd) is very tiny autoencoder which uses the same "latent API" as [SDXL-VAE](https://huggingface.co/stabilityai/sdxl-vae). |
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TAESDXL is useful for [real-time previewing](https://twitter.com/madebyollin/status/1679356448655163394) of the SDXL generation process. |
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Comparison on my laptop: |
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![image/jpeg](https://cdn-uploads.huggingface.co/production/uploads/630447d40547362a22a969a2/9iMkNdI1B9AC6vEpQTfTl.jpeg) |
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This repo contains `.safetensors` versions of the TAESDXL weights. |
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For SD1.x / SD2.x, use [TAESD](https://huggingface.co/madebyollin/taesd/) instead (the SD and SDXL VAEs are [incompatible](https://huggingface.co/madebyollin/sdxl-vae-fp16-fix/discussions/6#64b8a9c13707b7d603c6ac16)). |
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## Using in 🧨 diffusers |
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```python |
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import torch |
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from diffusers import DiffusionPipeline, AutoencoderTiny |
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pipe = DiffusionPipeline.from_pretrained( |
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"stabilityai/stable-diffusion-xl-base-1.0", torch_dtype=torch.float16 |
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) |
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pipe.vae = AutoencoderTiny.from_pretrained("madebyollin/taesdxl", torch_dtype=torch.float16) |
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pipe = pipe.to("cuda") |
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prompt = "slice of delicious New York-style berry cheesecake" |
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image = pipe(prompt, num_inference_steps=25).images[0] |
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image.save("cheesecake_sdxl.png") |
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``` |