Description
MOSS-Image-Base is a base model in the MOSS-Image family developed by OpenMOSS. It specializes in converting text prompts into images, supporting natural-language inputs, tag sequences, and JSON layouts. This model is designed to provide users with control over text placement and object arrangement within generated images.
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The model operates using Python 3.10 or later and requires an NVIDIA GPU with CUDA support. Users must install a compatible PyTorch 2.9 or later build. The model and its custom pipeline code are automatically downloaded and cached, although users can also provide a local model directory. The transformer and text encoder utilize bfloat16, while the VAE and initial noise use float32, with the bundled VAE employing the FLUX.2 small decoder.
MOSS-Image-Base offers a variety of sampling settings, including a default flow-matching Euler sampler, 50 steps, and a CFG of 3. Users can adjust these settings to suit their needs, such as disabling negative-branch skipping or providing a negative prompt. The model's prompt enhancer skill can turn image ideas into detailed captions or spatial layout prompts, designed for GPT-6-family agents.
For layout-to-image generation, users can pass a JSON layout as a prompt to describe scenes, rendered text, objects, and their positions. This allows for controlled editing and user-friendly layout tools, enabling adjustments to image content and composition. The model is released under the Apache License, Version 2.0, and acknowledges contributions from the Diffusers, Qwen, and FLUX teams.
- CategoryAI Image Generators
- Pricing ModelOpen source
- DeploymentCloud
- PlatformsWeb
MOSS-Image-Base Highlights
Base text-to-image model
Supports natural-language prompts
Tag sequences for text placement
JSON layouts for object arrangement
Python 3.10 or later required
NVIDIA GPU with CUDA support
Uses PyTorch 2.9 or later
FLUX.2 small decoder
Getting Started with MOSS-Image-Base
Access model: Visit Hugging Face page
Authenticate: Ensure account access
Set up environment: Install Python 3.10+ and CUDA-compatible PyTorch
Integrate via API: Use Python API for image generation
Optimize: Adjust sampling settings and prompts
MOSS-Image-Base's Use Cases
- Image Generation
- Layout Design
- Text Placement
- Object Arrangement
- Creative Projects
