--- 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'])