from diffusers import AutoPipelineForText2Image
import torch

pipeline = AutoPipelineForText2Image.from_pretrained('ai-toolkit/Wan2.2-T2V-A14B-Diffusers-bf16', torch_dtype=torch.bfloat16).to('cuda')
pipeline.load_lora_weights('synap5e/arcan3_251003_wan22-t2v_v12-rank32-lora', weight_name='arcan3_251003_wan22-t2v_v12-rank32_low_noise.safetensors')
image = pipeline('a beautiful landscape').images[0]
image.save("my_image.png")

For more details, including weighting, merging and fusing LoRAs, check the documentation on loading LoRAs in diffusers