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dc71583 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 | #!/usr/bin/env python3
"""Generate a demo image with NiT-XL."""
from pathlib import Path
import torch
from diffusers import DiffusionPipeline
REPO_ROOT = Path(__file__).resolve().parent
MODEL_DIR = REPO_ROOT / "NiT-XL"
OUTPUT_PATH = REPO_ROOT / "demo.png"
def main() -> None:
pipe = DiffusionPipeline.from_pretrained(
str(MODEL_DIR),
local_files_only=True,
custom_pipeline=str(MODEL_DIR / "pipeline.py"),
trust_remote_code=True,
torch_dtype=torch.bfloat16,
)
pipe.to("cuda")
pipe.set_progress_bar_config(disable=False)
print(pipe.id2label[207])
print(pipe.get_label_ids("golden retriever"))
generator = torch.Generator(device="cuda").manual_seed(42)
image = pipe(
class_labels="golden retriever",
height=512,
width=512,
num_inference_steps=250,
guidance_scale=2.05,
guidance_interval=(0.0, 0.7),
generator=generator,
).images[0]
image.save(OUTPUT_PATH)
print(f"Saved demo image to {OUTPUT_PATH}")
if __name__ == "__main__":
main()
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