import torch
from diffusers import DiffusionPipeline
# switch to "mps" for apple devices
pipe = DiffusionPipeline.from_pretrained("openai/consistency-decoder", dtype=torch.bfloat16, device_map="cuda")
prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k"
image = pipe(prompt).images[0]Consistency Decoder
This is a decoder that can be used to improve decoding for Stable Diffusion VAEs. To know more, refer to the DALL-E 3 technical report.
To original code repository can be found here.
Usage in 🧨 diffusers
import torch
from diffusers import DiffusionPipeline, ConsistencyDecoderVAE
vae = ConsistencyDecoderVAE.from_pretrained("openai/consistency-decoder", torch_dtype=pipe.torch_dtype)
pipe = StableDiffusionPipeline.from_pretrained(
"runwayml/stable-diffusion-v1-5", vae=vae, torch_dtype=torch.float16
).to("cuda")
pipe("horse", generator=torch.manual_seed(0)).images
Results
(Taken from the original code repository)
Examples
| Original Image | GAN Decoder | Consistency Decoder |
|---|---|---|
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