])

image = pipeline(
    prompt,
    source_embeds=src_embeds,
    target_embeds=target_embeds,
    num_inference_steps=50,
    cross_attention_guidance_amount=0.15,
).images[0]
image  Based on an input image When the pipeline is conditioned on an input image, we first obtain an inverted
noise from it using a DDIMInverseScheduler with the help of a generated caption. Then the inverted noise is used to start the generation process. First, let’s