from diffusers import AutoPipelineForText2Image
import torch

pipeline = AutoPipelineForText2Image.from_pretrained('black-forest-labs/FLUX.1-schnell', torch_dtype=torch.bfloat16).to('cuda')
pipeline.load_lora_weights('TFree2035/FluxScenario2', weight_name='loraSayed.safetensors')
image = pipeline('[trigger] ADscenario describing a left turn intersection. The ego vehicle wants to turn left').images[0]
image.save("my_image.png")

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