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/hf_repo_assets.py with huggingface_hub
Browse files- demo/hf_repo_assets.py +64 -0
demo/hf_repo_assets.py
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from __future__ import annotations
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import os
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from functools import lru_cache
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from pathlib import Path
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from huggingface_hub import snapshot_download
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def get_stage2_model_repo_id() -> str | None:
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return os.environ.get("SYNLAYERS_STAGE2_MODEL_REPO") or os.environ.get("SYNLAYERS_MODEL_REPO")
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def get_cache_dir() -> str | None:
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return os.environ.get("SYNLAYERS_HF_CACHE")
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@lru_cache(maxsize=4)
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def ensure_repo_assets(repo_id: str | None = None) -> Path | None:
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"""Download Stage 2 runtime assets from the configured model repo."""
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resolved_repo_id = repo_id or get_stage2_model_repo_id()
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if not resolved_repo_id:
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return None
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allow_patterns = [
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"SynLayers_checkpoints/FLUX.1-dev/**",
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"SynLayers_checkpoints/FLUX.1-dev-Controlnet-Inpainting-Alpha/**",
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"SynLayers_ckpt/step_120000/**",
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"ckpt/trans_vae/0008000.pt",
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"ckpt/pre_trained_LoRA/**",
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"ckpt/prism_ft_LoRA/**",
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]
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local_root = snapshot_download(
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repo_id=resolved_repo_id,
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repo_type="model",
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allow_patterns=allow_patterns,
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cache_dir=get_cache_dir(),
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)
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return Path(local_root)
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def build_repo_asset_overrides(repo_id: str | None = None) -> dict[str, str]:
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"""Return repo-local Stage 2 asset paths after downloading the uploaded bundle."""
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local_root = ensure_repo_assets(repo_id)
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if local_root is None:
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return {}
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overrides = {
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"repo_root": str(local_root),
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"decomp_ckpt_root": str(local_root / "SynLayers_ckpt" / "step_120000"),
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"pretrained_model_name_or_path": str(
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local_root / "SynLayers_checkpoints" / "FLUX.1-dev"
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),
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"pretrained_adapter_path": str(
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local_root
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/ "SynLayers_checkpoints"
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/ "FLUX.1-dev-Controlnet-Inpainting-Alpha"
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),
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"transp_vae_path": str(local_root / "ckpt" / "trans_vae" / "0008000.pt"),
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"pretrained_lora_dir": str(local_root / "ckpt" / "pre_trained_LoRA"),
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"artplus_lora_dir": str(local_root / "ckpt" / "prism_ft_LoRA"),
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}
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return overrides
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