Description
MOSS-Image-SFT is a sophisticated text-to-image model developed by OpenMOSS. It is part of the MOSS-Image family and is derived from the MOSS-Image-Base model. This model is designed to produce clearer text grouping and more organized layouts in generated images. It supports natural-language prompts, tag sequences, and JSON layouts, allowing users to control text placement and object arrangement effectively.
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The model requires Python 3.10 or later and an NVIDIA GPU with CUDA support for optimal performance. Users need to install a compatible PyTorch build and can download and cache the model and custom pipeline code automatically. The model uses bfloat16 for the transformer and text encoder, while the VAE and initial noise utilize float32.
MOSS-Image-SFT offers a Gradio interface and supports CPU offload and compilation options. Users can integrate it with ComfyUI by searching for MOSS-Image in the ComfyUI Manager. The model's default sampling settings include a flow-matching Euler sampler, 50 steps, and a CFG of 3, among others.
A notable feature is the MOSS-Image Prompt Enhancer, which converts image ideas into detailed captions or spatial layout prompts. This tool is designed for GPT-6-family agents and can convert pixel-coordinate drafts into compact JSON formats.
The model also supports layout-to-image generation, where users can pass a JSON layout as a prompt to describe scenes, rendered text, objects, and their positions. This feature allows for controlled editing and user-friendly layout tools, enabling adjustments to image content and composition in a structured manner.
- CategoryAI Models & LLMs
- Pricing ModelOpen source
- DeploymentCloud
- PlatformsWeb
MOSS-Image-SFT Highlights
Supervised fine-tuned text-to-image model
Supports natural-language prompts
Tag sequences for text placement
JSON layouts for object arrangement
Gradio interface available
Integration with ComfyUI
MOSS-Image Prompt Enhancer
Layout-to-image generation
Getting Started with MOSS-Image-SFT
Access model: Visit Hugging Face page
Authenticate: Ensure access to model
Set up environment: Install Python 3.10+ and CUDA-compatible PyTorch
Integrate via API: Use provided Python API
Optimize: Adjust sampling settings and layout prompts
MOSS-Image-SFT's Use Cases
- Text-to-Image Generation
- Layout Design
- Image Captioning
- Creative Design
- AI Art Creation
