er resolution

pipe = IFSuperResolutionPipeline.from_pretrained(
    "DeepFloyd/IF-II-L-v1.0", text_encoder=None, variant="fp16", torch_dtype=torch.float16, device_map="auto"
)

generator = torch.Generator().manual_seed(0)
stage_2_output = pipe(
    image=stage_1_output,
    prompt_embeds=prompt_embeds,
    negative_prompt_embeds=negative_embeds,
    output_type="pt",
    generator=generator,
).images

#pt_to_pil(stage_2_output)[0].save("./if_s