| #!/usr/bin/env python3 | |
| import torch | |
| from diffusers import AutoencoderKL, StableDiffusionXLPipeline, StableDiffusionXLImg2ImgPipeline, KDPM2AncestralDiscreteScheduler | |
| vae = AutoencoderKL.from_pretrained("madebyollin/sdxl-vae-fp16-fix", | |
| torch_dtype=torch.float16 | |
| ) | |
| base = StableDiffusionXLPipeline.from_pretrained("stabilityai/stable-diffusion-xl-base-1.0", | |
| vae=vae, | |
| torch_dtype=torch.float16, | |
| variant="fp16", | |
| use_safetensors=True | |
| ) | |
| scheduler = KDPM2AncestralDiscreteScheduler.from_config(base.scheduler.config, use_karras_sigmas=True) | |
| base.scheduler = scheduler | |
| base.to("cuda") | |
| def print_step(s, t, latents): | |
| print(s) | |
| generator=torch.manual_seed(1111) | |
| images = base( | |
| prompt="LOVE", | |
| num_inference_steps=10, | |
| generator=generator, | |
| callback=print_step | |
| ).images | |