ngers, long neck, username, watermark, signature"

generator = torch.Generator(device="cuda").manual_seed(43)

img_emb = prior_pipeline(prompt=prompt, image=img, strength=0.85, generator=generator)
negative_emb = prior_pipeline(prompt=negative_prior_prompt, image=img, strength=1, generator=generator) Now you can run the KandinskyV22ControlnetImg2ImgPipeline to generate an image from the initial image and the image embeddings:   Copied image = p