Hyper-SD
| Property | Value |
|---|---|
| Author | ByteDance |
| Paper | arXiv:2404.13686 |
| Tags | Text-to-Image, Diffusers, LoRA, Stable Diffusion |
What is Hyper-SD?
Hyper-SD is a state-of-the-art diffusion model acceleration technique that enables high-quality image generation in as few as 1-8 steps. It supports multiple base models including FLUX.1-dev, SD3-Medium, SDXL Base 1.0, and Stable-Diffusion v1-5 through efficient LoRA implementations.
Implementation Details
The model utilizes trajectory segmented consistency techniques to achieve rapid inference while maintaining image quality. It offers various checkpoint options including model-specific LoRAs and a unified approach supporting flexible step counts.
- Supports multiple inference steps (1-8) with a single unified LoRA
- Compatible with popular base models and ControlNet
- Implements specialized schedulers (TCDScheduler) for optimal results
- Offers both ComfyUI and Python API integration
Core Capabilities
- Ultra-fast inference with as few as 1-2 steps
- Flexible integration with existing workflows
- Support for both text-to-image and controlled generation
- Maintains high image quality despite reduced step count
Frequently Asked Questions
Q: What makes this model unique?
Hyper-SD stands out for its ability to generate high-quality images in significantly fewer steps than traditional diffusion models, while maintaining compatibility with popular base models and offering flexible implementation options.
Q: What are the recommended use cases?
The model is ideal for applications requiring fast image generation while maintaining quality, including rapid prototyping, real-time applications, and production environments where computational efficiency is crucial.
