generator = torch.manual_seed(0)
image = pipe(
    prompt=prompt, num_inference_steps=4, generator=generator, guidance_scale=8.0
).images[0]
image   ControlNet/T2I-Adapter Let’s look at how we can perform inference with ControlNet/T2I-Adapter and a LCM.  ControlNet

For this example, we'll use the [LCM_Dreamshaper_v7](https://huggingface.co/SimianLuo/LCM_Dreamshaper_v7) model with canny ControlNet, but the same steps can be applied to other LCM