README.md

---
license: mit
pipeline_tag: text-to-image
library_name: diffusers
datasets:
- pickapic-anonymous/pickapic_v1
---

This repository contains public models of [Latent Preference Optimization (LPO)](https://github.com/Kwai-Kolors/LPO) based on SD1.5 and SDXL. The merged models represent the merged weights of the LoRA weights with the original models.
The corresponding github repository is [https://github.com/Kwai-Kolors/LPO](https://github.com/Kwai-Kolors/LPO).


## 🛠️ Usage
### SDXL
```python
from diffusers import StableDiffusionXLPipeline, UNet2DConditionModel, AutoencoderKL
import torch

unet = UNet2DConditionModel.from_pretrained(
    'casiatao/LPO',
    subfolder="lpo_sdxl_merge/unet",
    torch_dtype=torch.float16
)
vae = AutoencoderKL.from_pretrained(
    'madebyollin/sdxl-vae-fp16-fix',
    torch_dtype=torch.float16,
)
pipe = StableDiffusionXLPipeline.from_pretrained(
    'stabilityai/stable-diffusion-xl-base-1.0', 
    unet=unet,
    vae=vae,
    torch_dtype=torch.float16
)
pipe = pipe.to("cuda")

prompt = "A cat holding a sign that says hello world"

generator=torch.Generator(device="cuda").manual_seed(42)
image = pipe(
    prompt=prompt,
    guidance_scale=5.0,
    num_inference_steps=20,
    generator=generator,
    output_type='pil',
).images[0]
image.save("img_sdxl.png")
```


### SD1.5
```python
from diffusers import StableDiffusionPipeline, UNet2DConditionModel
import torch

unet = UNet2DConditionModel.from_pretrained(
    'casiatao/LPO',
    subfolder="lpo_sd15_merge/unet",
    torch_dtype=torch.float16
)
pipe = StableDiffusionPipeline.from_pretrained(
    'sd-legacy/stable-diffusion-v1-5', 
    unet=unet,
    torch_dtype=torch.float16
)
pipe = pipe.to("cuda")

prompt = "a photo of a cat"

generator=torch.Generator(device="cuda").manual_seed(42)
image = pipe(
    prompt=prompt,
    guidance_scale=5.0,
    num_inference_steps=20,
    generator=generator,
    output_type='pil',
).images[0]
image.save("img_sd15.png")
```



## ❤️ Citation 
If you find this repository helpful, please consider giving it a like ❤️ and citing:
```bibtex
@article{zhang2025diffusion,
  title={Diffusion Model as a Noise-Aware Latent Reward Model for Step-Level Preference Optimization},
  author={Zhang, Tao and Da, Cheng and Ding, Kun and Jin, Kun and Li, Yan and Gao, Tingting and Zhang, Di and Xiang, Shiming and Pan, Chunhong},
  journal={arXiv preprint arXiv:2502.01051},
  year={2025}
}
```