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---
language:
- en
pipeline_tag: unconditional-image-generation
tags:
- Diffusion Models
- Stable Diffusion
- Perturbed-Attention Guidance
- PAG
---
# 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)
This repository is based on [Diffusers](https://huggingface.co/docs/diffusers/index). The pipeline is a modification of StableDiffusionPipeline to support Perturbed-Attention Guidance (PAG).
## Quickstart
Loading Custom Piepline:
```
from diffusers import StableDiffusionPipeline
pipe = StableDiffusionPipeline.from_pretrained(
"runwayml/stable-diffusion-v1-5",
custom_pipeline="hyoungwoncho/sd_perturbed_attention_guidance",
torch_dtype=torch.float16
)
device="cuda"
pipe = pipe.to(device)
```
Sampling with PAG:
```
output = pipe(
prompts,
width=512,
height=512,
num_inference_steps=50,
guidance_scale=0.0,
pag_scale=5.0,
pag_applied_layers_index=['m0']
).images
```
Sampling with PAG and CFG:
```
output = pipe(
prompts,
width=512,
height=512,
num_inference_steps=50,
guidance_scale=4.0,
pag_scale=3.0,
pag_applied_layers_index=['m0']
).images
```
## Parameters
guidance_scale : gudiance scale of CFG (ex: 7.5)
pag_scale : gudiance scale of PAG (ex: 5.0)
pag_applied_layers_index : index of the layer to apply perturbation (ex: ['m0'])
## Stable Diffusion Demo
To join a demo of PAG on Stable Diffusion, run [sd_pag_demo.ipynb](https://huggingface.co/hyoungwoncho/sd_perturbed_attention_guidance/blob/main/sd_pag_demo.ipynb).
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