Image-to-Image
Diffusers
Safetensors
image-decomposition
layered-image-editing
diffusion
flux
lora
transparent-rgba
Instructions to use SynLayers/synlayers with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use SynLayers/synlayers with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline from diffusers.utils import load_image # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("fill-in-base-model", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("SynLayers/synlayers") prompt = "Turn this cat into a dog" input_image = load_image("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/cat.png") image = pipe(image=input_image, prompt=prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
Upload demo/publish_space.py with huggingface_hub
Browse files- demo/publish_space.py +82 -0
demo/publish_space.py
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from __future__ import annotations
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import argparse
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import os
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from pathlib import Path
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from huggingface_hub import HfApi
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PROJECT_ROOT = Path(__file__).resolve().parents[1]
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STATIC_FILE_MAP = {
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PROJECT_ROOT / "demo" / "__init__.py": "demo/__init__.py",
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PROJECT_ROOT / "demo" / "app.py": "app.py",
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PROJECT_ROOT / "demo" / "hf_repo_assets.py": "demo/hf_repo_assets.py",
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PROJECT_ROOT / "demo" / "README.md": "README.md",
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PROJECT_ROOT / "demo" / "publish_space.py": "demo/publish_space.py",
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PROJECT_ROOT / "demo" / "requirements-hf-space.txt": "requirements.txt",
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PROJECT_ROOT / "demo" / "real_world_pipeline.py": "demo/real_world_pipeline.py",
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PROJECT_ROOT / "demo" / "upload_used_bundle_to_hf.py": "demo/upload_used_bundle_to_hf.py",
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PROJECT_ROOT / "demo" / "infer" / "__init__.py": "demo/infer/__init__.py",
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PROJECT_ROOT / "demo" / "infer" / "run_caption_bbox_infer.py": "demo/infer/run_caption_bbox_infer.py",
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PROJECT_ROOT / "demo" / "infer" / "vlm_bbox_inference.py": "demo/infer/vlm_bbox_inference.py",
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PROJECT_ROOT / "infer" / "__init__.py": "infer/__init__.py",
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PROJECT_ROOT / "infer" / "common_infer.py": "infer/common_infer.py",
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PROJECT_ROOT / "infer" / "infer.py": "infer/infer.py",
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PROJECT_ROOT / "infer" / "infer.yaml": "infer/infer.yaml",
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PROJECT_ROOT / "models" / "__init__.py": "models/__init__.py",
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PROJECT_ROOT / "models" / "mmdit.py": "models/mmdit.py",
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PROJECT_ROOT / "models" / "multiLayer_adapter.py": "models/multiLayer_adapter.py",
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PROJECT_ROOT / "models" / "pipeline.py": "models/pipeline.py",
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PROJECT_ROOT / "models" / "transp_vae.py": "models/transp_vae.py",
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PROJECT_ROOT / "tools" / "__init__.py": "tools/__init__.py",
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PROJECT_ROOT / "tools" / "tools.py": "tools/tools.py",
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}
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def iter_uploads():
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for local_path, remote_path in STATIC_FILE_MAP.items():
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if local_path.exists():
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yield local_path, remote_path
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def main():
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parser = argparse.ArgumentParser(
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description="Create or update a Hugging Face Space for the SynLayers demo."
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)
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parser.add_argument("--repo-id", type=str, required=True, help="Target Space repo id, e.g. SynLayers/synlayers-demo")
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parser.add_argument("--token", type=str, default=os.environ.get("HF_TOKEN"))
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parser.add_argument("--private", action="store_true", help="Create the Space as private")
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args = parser.parse_args()
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if not args.token:
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raise ValueError("Missing Hugging Face token. Pass --token or set HF_TOKEN.")
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api = HfApi(token=args.token)
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api.create_repo(
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repo_id=args.repo_id,
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repo_type="space",
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private=args.private,
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space_sdk="gradio",
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exist_ok=True,
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)
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for local_path, remote_path in iter_uploads():
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print(f"Uploading {local_path} -> {remote_path}")
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api.upload_file(
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path_or_fileobj=str(local_path),
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path_in_repo=remote_path,
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repo_id=args.repo_id,
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repo_type="space",
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)
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print("")
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print(f"Space scaffold uploaded to https://huggingface.co/spaces/{args.repo_id}")
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print("Model assets are not uploaded by this helper.")
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print("Configure the Space variables before running:")
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print(" SYNLAYERS_BBOX_MODEL_REPO=SynLayers/Bbox-caption-8b")
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print(" SYNLAYERS_STAGE2_MODEL_REPO=SynLayers/synlayers")
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if __name__ == "__main__":
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main()
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