To use PAG with ControlNet, first create a `controlnet`. Then, pass the `controlnet` and other PAG arguments to the `from_pretrained` method of the AutoPipeline for the specified task.  
```py
from diffusers import AutoPipelineForText2Image, ControlNetModel
import torch

controlnet = ControlNetModel.from_pretrained(
"diffusers/controlnet-canny-sdxl-1.0", torch_dtype=torch.float16
)

pipeline = AutoPipelineForText2Image.from_pretrained(
"stabilityai/stable-diffusion-xl-base-1.0",
controlnet=controlnet,
enable_pag=True,
pag_applied_layers="mid",
torch_dtype=torch.float16
)
pipeline.enable_model_cpu_offload()
```  
<Tip>  
If you already have a controlnet pipeline and want to enable PAG, you can use the `from_pipe` API: `AutoPipelineForText2Image.from_pipe(pipeline_controlnet, enable_pag=True)`  
</Tip>  
You can use the pipeline in the same way you normally use ControlNet pipelines, with the added option to specify a `pag_scale` parameter. Note that PAG works well for unconditional generation. In this example, we will generate an image without a prompt.  
```py
from diffusers.utils import load_image
canny_image = load_image(
"https://huggingface.co/datasets/YiYiXu/testing-images/resolve/main/pag_control_input.png"
)

for pag_scale in [0.0, 3.0]:
generator = torch.Generator(device="cpu").manual_seed(1)
images = pipeline(
prompt="",
controlnet_conditioning_scale=controlnet_conditioning_scale,
image=canny_image,
num_inference_steps=50,
guidance_scale=0,
generator=generator,
pag_scale=pag_scale,
).images
images[0]
```  
<div class="flex flex-row gap-4">
<div class="flex-1">
<img class="rounded-xl" src="https://huggingface.co/datasets/YiYiXu/testing-images/resolve/main/pag_0.0_controlnet.png"/>
<figcaption class="mt-2 text-center text-sm text-gray-500">generated image without PAG</figcaption>
</div>
<div class="flex-1">
<img class="rounded-xl" src="https://huggingface.co/datasets/YiYiXu/testing-images/resolve/main/pag_3.0_controlnet.png"/>
<figcaption class="mt-2 text-center text-sm text-gray-500">generated image with PAG</figcaption>
</div>
</div>
/Users/nielsrogge/Documents/python_projecten/diffusers/docs/source/en/using-diffusers/pag.md