π° Tiny AutoEncoder for Stable Diffusion
TAESD is very tiny autoencoder which uses the same "latent API" as Stable Diffusion's VAE. TAESD is useful for real-time previewing of the SD generation process.
Comparison on my laptop:
This repo contains .safetensors
versions of the TAESD weights.
For SDXL, use TAESDXL instead (the SD and SDXL VAEs are incompatible).
Using in 𧨠diffusers
import torch
from diffusers import DiffusionPipeline, AutoencoderTiny
pipe = 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.save("cheesecake.png")
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