apply_lora_example.py

from diffusers import StableDiffusionPipeline, DPMSolverMultistepScheduler
from torch
from PIL import Image

def image_grid(imgs, rows, cols):
    assert len(imgs) == rows*cols

    w, h = imgs[0].size
    grid = Image.new('RGB', size=(cols*w, rows*h))
    grid_w, grid_h = grid.size
    
    for i, img in enumerate(imgs):
        grid.paste(img, box=(i%cols*w, i//cols*h))
    return grid
    
pipe = StableDiffusionPipeline.from_ckpt('https://huggingface.co/gsdf/Counterfeit-V3.0/blob/main/Counterfeit-V3.0_fp16.safetensors', 
                                         torch_dtype=torch.float16, 
                                         safety_checker=None).to('cuda')
pipe.scheduler = DPMSolverMultistepScheduler.from_config(pipe.scheduler.config, use_karras_sigmas=True)
pipe.enable_xformers_memory_efficient_attention()

prompt = "masterpiece, best quality, 1girl, at dusk"
negative_prompt = ("(low quality, worst quality:1.4), (bad anatomy), (inaccurate limb:1.2), "
                   "bad composition, inaccurate eyes, extra digit, fewer digits, (extra arms:1.2), large breasts")

import kohya_lora_loader
kohya_lora_loader.install_lora_hook(pipe)
lora1 = pipe.apply_lora('Light_and_Shadow.safetensors')

images = pipe(prompt=prompt, 
     negative_prompt=negative_prompt, 
     width=512, 
     height=768, 
     num_inference_steps=15, 
     num_images_per_prompt=4,
     generator=torch.Generator(device='cuda').manual_seed(0)).images
image_grid(images, 1, 4)