OpenMOSS/MOSS-Image

选用指南

AI 根据 README 整理 · 2026/10/16 17:41:18

使用方式

可通过 Python API 或 Gradio 界面使用，也提供 ComfyUI 插件。

查看 README 依据

- 🛠️ **Easy to fine-tune:** Adapt the base model to custom tasks and domains. - ⚡ **Compact and efficient:** Efficient image generation with a 5B backbone. - 🖥️ **Heterogeneous GPU training**: Trained on alternative GPU platforms. <a id="user-guide"></a> ## User guide Start with the **[English user guide](USERGUIDE.md)** or **[中文用户指南](USERGUIDE_ZH.md)** for recommended inference settings, prompt examples, layout input formats, and LoRA training guidance. <a id="comfyui"></a> ## ComfyUI This repository provides a native MOSS-Image plugin for ComfyUI.

|  |  | <!-- MOSS-Image-Base uses a 42-layer diffusion transformer, a Qwen3.5-9B text encoder, and a FLUX.2 VAE. --> <a id="quick-start"></a> ## 🚀 Quick start <a id="installation"></a> ### 🛠️ Installation ```bash git clone https://github.com/OpenMOSS/MOSS-Image.git cd MOSS-Image python -m venv .venv source .venv/bin/activate pip install -r requirements.txt ``` <a id="python"></a> ### 🐍 Python ```python import torch from diffusers import DiffusionPipeline

uncond_skip_layers=[22], generator=torch.Generator("cpu").manual_seed(42), ).images[0] image.save("refrigerator_note.png") ``` <a id="gradio"></a> ### 🎨 Gradio ```bash pip install -e '.[ui]' python gradio_app.py --model OpenMOSS-Team/MOSS-Image-Base ``` <a id="sampling-settings"></a> ### 🎛️ Sampling settings | Setting | Default | | --- | --- | | Sampler | Flow-matching Euler | | Steps | 50 | | CFG | 3 | | Shift | 5 | | Layer skipping | Negative-branch skipping at layer 22 | | Negative prompt (Python API) | Empty |

部署要求

需要 Python 环境，安装依赖后使用，模型需从 Hugging Face 或 ModelScope 下载。

查看 README 依据

|  |  | <!-- MOSS-Image-Base uses a 42-layer diffusion transformer, a Qwen3.5-9B text encoder, and a FLUX.2 VAE. --> <a id="quick-start"></a> ## 🚀 Quick start <a id="installation"></a> ### 🛠️ Installation ```bash git clone https://github.com/OpenMOSS/MOSS-Image.git cd MOSS-Image python -m venv .venv source .venv/bin/activate pip install -r requirements.txt ``` <a id="python"></a> ### 🐍 Python ```python import torch from diffusers import DiffusionPipeline

已知限制

GPU 内存不足时需选择 Sequential 模式或降低图像尺寸，编译 DiT 在 Sequential 模式下不可用。

查看 README 依据

See the [user guide](USERGUIDE.md) for sampling and prompt recommendations. <a id="memory-and-performance"></a> ### ⚡ Memory and performance Select Memory mode in Gradio's Advanced settings: | Mode | Behavior | | --- | --- | | GPU resident | Keep the entire model on GPU | | Component | Move model components between CPU and GPU as needed | | Sequential · fallback | Lower memory use with slower inference | If GPU memory is insufficient, select Sequential or reduce image size. Compile DiT is disabled by default and unavailable in Sequential mode. <a id="layout-generation"></a>