AnimateDiff-Lightning
| Property | Value |
|---|---|
| Author | ByteDance |
| License | CreativeML OpenRAIL-M |
| Research Paper | AnimateDiff-Lightning: Cross-Model Diffusion Distillation |
| Downloads | 75,542 |
What is AnimateDiff-Lightning?
AnimateDiff-Lightning is a revolutionary text-to-video generation model that achieves remarkable speed improvements over its predecessor. Developed by ByteDance, this model can generate videos more than ten times faster than the original AnimateDiff through innovative cross-model diffusion distillation techniques. It offers multiple inference step options (1, 2, 4, and 8 steps), with the 2, 4, and 8-step variants producing particularly high-quality results.
Implementation Details
The model is built on the Diffusers framework and has been distilled from AnimateDiff SD1.5 v2. It supports both text-to-video and video-to-video generation capabilities, with particular optimization for stylized base models.
- Multiple step variants for different speed/quality tradeoffs
- Compatible with various base models including epiCRealism and ToonYou
- Supports Motion LoRAs with recommended strength of 0.7~0.8
- Implements EulerDiscreteScheduler with trailing timestep spacing
Core Capabilities
- Ultra-fast video generation with minimal quality loss
- Flexible integration with popular base models
- Support for both text-to-video and video-to-video workflows
- ComfyUI compatibility with specialized workflows
- ControlNet support for enhanced video-to-video generation
Frequently Asked Questions
Q: What makes this model unique?
The model's primary distinction is its ability to generate high-quality animated content at speeds up to 10x faster than traditional methods, while maintaining impressive quality through distillation techniques.
Q: What are the recommended use cases?
The model excels in creating animated content from both text descriptions and existing videos. It's particularly effective when used with stylized base models for both realistic and anime-style content generation, making it suitable for creative professionals and content creators.
