pipeline = SanaPipeline.from_pretrained(
"Efficient-Large-Model/Sana_1600M_1024px_diffusers",
text_encoder=text_encoder_8bit,
transformer=transformer_8bit,
torch_dtype=torch.float16,
device_map="balanced",
)

prompt = "a tiny astronaut hatching from an egg on the moon"
image = pipeline(prompt).images[0]
image.save("sana.png")
```