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license: mit |
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# 🍰 Tiny AutoEncoder for Stable Diffusion 3 |
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[TAESD3](https://github.com/madebyollin/taesd) is very tiny autoencoder which uses the same "latent API" as Stable Diffusion 3's VAE. |
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TAESD3 is useful for real-time previewing of the SD3 generation process. |
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This repo contains `.safetensors` versions of the TAESD3 weights. |
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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 StableDiffusion3Pipeline, AutoencoderTiny |
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pipe = StableDiffusion3Pipeline.from_pretrained( |
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"stabilityai/stable-diffusion-3-medium-diffusers", torch_dtype=torch.float16 |
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) |
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pipe.vae = AutoencoderTiny.from_pretrained("madebyollin/taesd3", torch_dtype=torch.float16) |
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pipe.vae.config.shift_factor = 0.0 |
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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.png") |
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``` |
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<img width=512 src=https://cdn-uploads.huggingface.co/production/uploads/630447d40547362a22a969a2/vxm-Ek_N9eMVurl5yf5Jz.png /> |
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