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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 |