TinyBreaker

Overview

TinyBreaker is a hybrid model designed for efficient image generation even on mid and low-end hardware! By integrating the strengths of both PixArt and SD1.5 (Photon) models, TinyBreaker offers an elegant solution that doesn't compromise on quality or performance.

Key Features

Hybrid Model Architecture: Combines base image generation with PixArt and refinement using Photon (or any SD1 model), optimized for minimal parameter use.
Efficient Parameter Use: A lean 0.6 billion parameters in the base model enable high-quality images without hefty computational demands.
Quick Performance: Generate stunning images of size 1536×1024 in approximately ~12 seconds on an NVIDIA RTX 3080 GPU, with ongoing efforts to achieve sub-10-second generation times.
High Prompt Adherence: Ensures generated images are closely aligned with user instructions and expectations due to PixArt model integration.
Optimized Latent Space Handling: Utilizes Tiny Autoencoders for efficient latent space conversion, streamlining the input-to-image process.

Current Usage

TinyBreaker is currently utilizable via ComfyUI. To use TinyBreaker, you'll need to install custom nodes specific to this model through ComfyUI-TinyBreaker on GitHub.

Note: The current prototype0 version of TinyBreaker utilizes PixArt Sigma 1024 + Photon (SD1.5) without additional training or fine-tuning.

Limitations

Text Generation: Currently, generating legible text within images is a challenge due to PixArt's training limitations. Enhancements in this area may require extensive retraining.

Future Directions

I'm dedicated to enhancing TinyBreaker's speed and accessibility, particularly for users with mid-range or lower-end hardware setups. Look forward to future updates as I work on enhancing TinyBreaker's capabilities.