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from diffusers import AutoPipelineForText2Image | |
import torch | |
from diffusers import StableDiffusionControlNetPipeline, ControlNetModel, UniPCMultistepScheduler | |
from diffusers import StableDiffusionXLControlNetPipeline, ControlNetModel, AutoencoderKL | |
import torch | |
from PIL import Image | |
def get_pipe(lora_dir): | |
controlnets = [ControlNetModel.from_pretrained("mattyamonaca/white2line", torch_dtype=torch.float16)] | |
vae = AutoencoderKL.from_pretrained("madebyollin/sdxl-vae-fp16-fix", torch_dtype=torch.float16) | |
pipe = StableDiffusionXLControlNetPipeline.from_pretrained( | |
"cagliostrolab/animagine-xl-3.1", controlnet=controlnets, vae=vae, torch_dtype=torch.float16 | |
) | |
pipe.enable_model_cpu_offload() | |
pipe.load_lora_weights(lora_dir, weight_name="sdxl_BWLine.safetensors") | |
return pipe |