Vargol/lcm_sdxl_full_model

This is a copy of the sdxl base (stabilityai/stable-diffusion-xl-base-1.0) with the unet replaced with the LCM distilled unet (latent-consistency/lcm-sdxl) and scheduler config set to default to the LCM Scheduler.

This makes LCM SDXL run as a standard Diffusion Pipeline

from diffusers import DiffusionPipeline
import torch

pipe = DiffusionPipeline.from_pretrained(
    "Vargol/lcm_sdxl_full_model", variant='fp16', torch_dtype=torch.float16
).to("mps")

prompt = "Self-portrait oil painting, a beautiful cyborg with golden hair, 8k"
generator = torch.manual_seed(0)

image = pipe(
    prompt=prompt, num_inference_steps=4, generator=generator, guidance_scale=8.0
).images[0]

image.save('distilled.png')