.py

from diffusers import AutoPipelineForImage2Image

CACHE_DIR = "."
DEVICE = "cuda:0"

pipe = AutoPipelineForImage2Image.from_pretrained(
    "runwayml/stable-diffusion-v1-5", 
    torch_dtype=torch.float16,
    variant="fp16",
    use_safetensors=True,
    cache_dir=CACHE_DIR
).to(DEVICE)

prompt = "New modern style of livingroom, warm color palette, detailed, 8k"
img_gen = pipe(prompt, image=img_pil.resize((512, 512)), strenght=0.7, num_inference_steps=100)
img_gen.images[0]