| ```py | |
| from diffusers import UNet2DConditionModel, DiffusionPipeline, LCMScheduler | |
| unet = UNet2DConditionModel.from_pretrained("latent-consistency/lcm-sdxl", torch_dtype=torch.float16, variant="fp16") | |
| pipe = DiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-xl-base-1.0", unet=unet, torch_dtype=torch.float16, variant="fp16") | |
| pipe.scheduler = LCMScheduler.from_config(sd_pipe.scheduler.config) | |
| pipe.set_progress_bar_config(disable=None) | |
| prompt = "a red car standing on the side of the street" | |
| image = pipe(prompt, num_inference_steps=4, guidance_scale=8.0).images[0] | |
| ``` |