line
torch.manual_seed(0)
image = pipe(
    prompt=prompt,
    source_prompt=source_prompt,
    image=init_image,
    num_inference_steps=100,
    eta=0.1,
    strength=0.85,
    guidance_scale=3,
    source_guidance_scale=1,
).images[0]

image.save("black_to_blue.png")

CycleDiffusionPipeline
	

class diffusers.CycleDiffusionPipeline

<
source
>
(
vae: AutoencoderKL
text_encoder: CLIPTextModel
tokenizer: CLIPTokenizer
unet: UNet2DConditionMode