tiny-sd
| Property | Value |
|---|---|
| License | CreativeML OpenRAIL-M |
| Base Model | SG161222/Realistic_Vision_V4.0 |
| Research Paper | View Paper |
| Training Dataset | LAION-art-EN-improved-captions |
What is tiny-sd?
tiny-sd is a distilled version of the Stable Diffusion model, specifically optimized for high-performance text-to-image generation. Built upon Realistic Vision V4.0, this model achieves up to 80% faster inference speeds while maintaining impressive image generation quality.
Implementation Details
The model was trained with specific hyperparameters including 125,000 steps, a learning rate of 1e-4, and batch size of 32. It operates at 512 resolution and utilizes mixed-precision fp16 for optimal performance. The implementation is available through the Diffusers pipeline, making it easily accessible for practical applications.
- Gradient accumulation steps: 4
- Mixed-precision training with fp16
- Optimized for 512x512 resolution
- Compatible with Diffusers pipeline
Core Capabilities
- High-speed text-to-image generation
- Up to 80% faster than base SD1.5 models
- Maintains quality while reducing computational overhead
- Easy integration with existing pipelines
Frequently Asked Questions
Q: What makes this model unique?
The model's primary distinction is its significant speed improvement while maintaining generation quality, achieved through careful distillation of Realistic Vision V4.0. It offers an 80% speed boost compared to base SD1.5 models, making it ideal for production environments.
Q: What are the recommended use cases?
This model is particularly suited for applications requiring fast inference times, such as real-time image generation services, batch processing systems, and resource-constrained environments. It's ideal for developers looking to implement efficient text-to-image generation without sacrificing quality.
