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---
license:
- apache-2.0
language:
- en
tags:
- Diffusion Models
- Stable Diffusion XL
- Perturbed-Attention Guidance
- PAG
---
# Perturbed-Attention Guidance for SDXL (i2i)
The original Perturbed-Attention Guidance for unconditional models and SD1.5 by [Hyoungwon Cho](https://huggingface.co/hyoungwoncho) is availiable at [hyoungwoncho/sd_perturbed_attention_guidance](https://huggingface.co/hyoungwoncho/sd_perturbed_attention_guidance)
[Project](https://ku-cvlab.github.io/Perturbed-Attention-Guidance/) / [arXiv](https://arxiv.org/abs/2403.17377) / [GitHub](https://github.com/KU-CVLAB/Perturbed-Attention-Guidance)
Also there is an extra implementation of the Perturbed-Attention Guidance (PAG) on Stable Diffusion XL (SDXL) for the 🧨 diffusers library by [multimodalart](https://huggingface.co/multimodalart)
[code](https://huggingface.co/multimodalart/sdxl_perturbed_attention_guidance) / [demo](https://huggingface.co/spaces/multimodalart/perturbed-attention-guidance-sdxl)
This repository is just a simple implementation of the Perturbed-Attention Guidance (PAG) on Stable Diffusion XL (SDXL) for the 🧨 diffusers library to "image-to-image".
## Quickstart
Loading Custom Pipeline:
```py
from diffusers import StableDiffusionXLImg2ImgPipeline
pipe = StableDiffusionXLImg2ImgPipeline.from_pretrained(
"stabilityai/stable-diffusion-xl-base-1.0",
custom_pipeline="jyoung105/sdxl_perturbed_attention_guidance_i2i",
torch_dtype=torch.float16
)
device="cuda"
pipe = pipe.to(device)
```
Unconditional sampling with PAG:
![image](example 1.png)
```py
output = pipe(
"",
image=init_image,
strength=0.6,
num_inference_steps=40,
guidance_scale=0.0,
pag_scale=4.0,
pag_applied_layers=['mid']
).images
```
Sampling with PAG and CFG:
![image](example 2.png)
```py
output = pipe(
"A man with hoodie on is looking at sky, photo",
image=init_image,
strength=0.6,
num_inference_steps=40,
guidance_scale=4.0,
pag_scale=3.0,
pag_applied_layers=['mid']
).images
```
## Parameters
`guidance_scale` : guidance scale of CFG (ex: `7.5`)
`pag_scale` : guidance scale of PAG (ex: `4.0`)
`pag_applied_layers`: layer to apply perturbation (ex: ['mid'])
`pag_applied_layers_index` : index of the layers to apply perturbation (ex: ['m0', 'm1'])