SDXS-512-DreamShaper-Anime
SDXS is a model that can generate high-resolution images in real-time based on prompt texts, trained using score distillation and feature matching. For more information, please refer to our research paper: SDXS: Real-Time One-Step Latent Diffusion Models with Image Conditions. We open-source the model as part of the research.
SDXS-512-DreamShaper-Anime is the anime-style LoRA for SDXS-512-DreamShaper. Watch our repo for any updates.
Diffusers Usage
import torch
from diffusers import StableDiffusionPipeline
import peft
repo = "IDKiro/sdxs-512-dreamshaper"
lora_repo = "IDKiro/sdxs-512-dreamshaper-anime"
weight_type = torch.float16 # or float32
# Load model.
pipe = StableDiffusionPipeline.from_pretrained(repo, torch_dtype=weight_type)
pipe.unet = PeftModel.from_pretrained(pipe.unet, lora_repo)
pipe.to("cuda")
prompt = "Self-portrait oil painting, a beautiful cyborg with golden hair, 8k"
# Ensure using 1 inference step and CFG set to 0.
image = pipe(
prompt,
num_inference_steps=1,
guidance_scale=0
).images[0]
image.save("output.png")
Cite Our Work
@article{song2024sdxs,
author = {Yuda Song, Zehao Sun, Xuanwu Yin},
title = {SDXS: Real-Time One-Step Latent Diffusion Models with Image Conditions},
journal = {arxiv},
year = {2024},
}
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