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---
license: openrail++
tags:
- text-to-image
- stable-diffusion
library_name: diffusers
inference: false
---
# 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](https://arxiv.org/abs/2403.16627).
We open-source the model as part of the research.
SDXS-512-DreamShaper-Anime is the anime-style **LoRA** for [SDXS-512-DreamShaper](https://huggingface.co/IDKiro/sdxs-512-dreamshaper).
Watch [our repo](https://github.com/IDKiro/sdxs) for any updates.
## Diffusers Usage
```python
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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