🎉Glad to announce SANA-Sprint is available!

[lawrence-cj]

Our SANA-Sprint models focus on timestep distillation, achieving high-quality generation with 1-4 inference steps. Refer to SANA-Sprint Manual for more details.

After the PR merged: https://github.com/huggingface/diffusers/pull/11074

pip install git+https://github.com/huggingface/diffusers

# test sana sprint
from diffusers import SanaSprintPipeline
import torch

pipeline = SanaSprintPipeline.from_pretrained(
    "Efficient-Large-Model/Sana_Sprint_1.6B_1024px_diffusers",
    torch_dtype=torch.bfloat16
)
pipeline.to("cuda:0")

prompt = "a tiny astronaut hatching from an egg on the moon"

image = pipeline(prompt=prompt, num_inference_steps=2).images[0]
image.save("test_out.png")