Image-to-Image
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Safetensors
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- # Stable Layers — Inference
 
 
 
 
 
 
 
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- Project Page: https://stability-ai.github.io/stable-layers.github.io/
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- Paper: https://arxiv.org/abs/2605.30257
 
 
 
 
 
 
 
 
 
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- Note: whilst the paper used gemini, this model was retrained using an open VLM, we found no performance loss.
 
 
 
 
 
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- ---
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- ## Recommended inference settings
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-
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- > ### **Heun sampler · 50 steps · CFG 1.0 · 640 px · 4 layers**
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- | Setting | Value | Flag |
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- |---|---|---|
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- | **Sampler** | **Heun (2nd order)** | always used — not configurable |
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- | **Steps** | **50** | `--steps 50` |
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- | **CFG / guidance** | **1.0 (off)** | `--guidance-scale 1.0` |
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- | Resolution | 640 px (max dim) | `--size 640` |
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- | Layers | 4 | `--num-layers 4` |
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- **Note:** with using a high resolution or lower steps or not heun will garble the results.
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- ---
 
 
 
 
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- ## Install
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  ```bash
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  pip install torch diffusers transformers peft pillow numpy
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  Requires **one GPU** — the base model is ~40 GB in bf16, so an 80 GB-class card
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  (A100-80 / H100 / H200) is comfortable.
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- ---
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- ## Weights
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- The base model is pulled from HuggingFace automatically
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- (`Qwen/Qwen-Image-Layered`). Lora found locally.
 
 
 
 
 
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- ---
 
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- ## Usage
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  ```bash
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  # single image
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  python decompose.py --input photo.png --output results/ --lora ./model
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  ```
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- ---
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-
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- ## Output
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  ```
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  results/<image_name>/
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  `--transparent` to get **RGBA with real alpha**, which is what you want when
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  importing into an editor or compositing them yourself.
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- ---
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-
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- ## Notes
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  - **Reproducible:** noise is seeded per image as `seed + image_index`
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  (`--seed 42` by default), so the same inputs give the same outputs.
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  override with `--prompt` if you want.
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  - **Aspect ratio** is preserved; the longest side is scaled to `--size` and both
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  dimensions are rounded to multiples of 16.
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ ---
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+ license: other
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+ license_name: stabilityai-community
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+ license_link: https://stability.ai/license
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+ base_model: Qwen/Qwen-Image-Layered
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+ library_name: peft
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+ pipeline_tag: image-to-image
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+ ---
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+ <h1 align="center">Stable Layers</h1>
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+ <p align="center">
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+ <strong>Decomposing Images into Editable RGBA Layers</strong>
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+ </p>
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+
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+ <!-- Add a teaser image to the repo and it will render here. -->
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+ <!--
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+ <p align="center">
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+ <img src="stable_layers_teaser.jpg" alt="Stable Layers Teaser" width="100%" />
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+ </p>
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+ -->
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+ <p align="center">
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+ <span><a href="https://arxiv.org/abs/2605.30257">Paper</a></span>&nbsp;&nbsp;&nbsp;
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+ <span><a href="https://stability-ai.github.io/stable-layers.github.io/">Project Page</a></span>&nbsp;&nbsp;&nbsp;
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+ <span><a href="https://huggingface.co/StabilityLabs/Stable-Layers">Model (Hugging Face)</a></span>&nbsp;&nbsp;&nbsp;
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+ <span><a href="https://github.com/Stability-AI/Stable-Layers">Code</a></span>
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+ </p>
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+ ## About
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+ **Stable Layers** decomposes a single RGB image into a small stack of back-to-front
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+ RGBA layers (background plus object layers) suitable for compositing and editing.
 
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+ This repository hosts the LoRA adapter over `Qwen/Qwen-Image-Layered`. Note: whilst
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+ the paper used Gemini, this model was retrained using an open VLM, and we found no
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+ performance loss.
 
 
 
 
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+ ## Model Artifacts
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+ This repository **is** the LoRA adapter (`adapter_config.json`,
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+ `adapter_model.safetensors`). The base model is pulled from Hugging Face
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+ automatically (`Qwen/Qwen-Image-Layered`). See the
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+ [code repository](https://github.com/Stability-AI/Stable-Layers) for the inference
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+ script.
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+ ## Installation
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  ```bash
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  pip install torch diffusers transformers peft pillow numpy
 
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  Requires **one GPU** — the base model is ~40 GB in bf16, so an 80 GB-class card
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  (A100-80 / H100 / H200) is comfortable.
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+ ## Recommended Inference Settings
58
 
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+ > ### **Heun sampler · 50 steps · CFG 1.0 · 640 px · 4 layers**
60
 
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+ | Setting | Value | Flag |
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+ |---|---|---|
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+ | **Sampler** | **Heun (2nd order)** | always used — not configurable |
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+ | **Steps** | **50** | `--steps 50` |
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+ | **CFG / guidance** | **1.0 (off)** | `--guidance-scale 1.0` |
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+ | Resolution | 640 px (max dim) | `--size 640` |
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+ | Layers | 4 | `--num-layers 4` |
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+ **Note:** using a higher resolution, lower steps, or a non-Heun sampler will garble
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+ the results.
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+ ## Quickstart
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  ```bash
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  # single image
 
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  python decompose.py --input photo.png --output results/ --lora ./model
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  ```
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+ ## Outputs
 
 
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  ```
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  results/<image_name>/
 
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  `--transparent` to get **RGBA with real alpha**, which is what you want when
106
  importing into an editor or compositing them yourself.
107
 
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+ **Notes:**
 
 
109
 
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  - **Reproducible:** noise is seeded per image as `seed + image_index`
111
  (`--seed 42` by default), so the same inputs give the same outputs.
 
114
  override with `--prompt` if you want.
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  - **Aspect ratio** is preserved; the longest side is scaled to `--size` and both
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  dimensions are rounded to multiples of 16.
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+
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+ ## License
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+
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+ This code and model usage are subject to Stability AI Community License terms.
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+
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+ For individuals or organizations generating annual revenue of USD 1,000,000 (or local
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+ currency equivalent) or more, commercial usage requires an enterprise license from
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+ Stability AI.
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+
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+ - License details: https://stability.ai/license
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+ - Enterprise request: https://stability.ai/enterprise
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+
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+ ## Citation
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+
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+ ```
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+ @article{stablelayers2026,
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+ author = {},
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+ title = {Stable Layers: Decomposing Images into Editable RGBA Layers},
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+ journal = {arXiv preprint arXiv:2605.30257},
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+ year = {2026}
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+ }
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+ ```