bria/fibo-lite/generate

Overview

Fibo Lite, the new addition to the Fibo model family, allows generating high-quality images with the same controllability of the JSON structured prompt, while using significantly fewer inference steps, resulting in significantly improved latency.

This is a two-stage distilled model for the FIBO text-to-image model, combining:

1. CFG Distillation: First, we distill classifier-free guidance into the model, enabling inference with Guidance Scale = 1.0 (skipping the negative prompt pass).
2. SCFM (Shortcutting Flow Matching): On top of the CFG-distilled merged model, we apply velocity field self-distillation to enable efficient few-step sampling.

🔑 Key Benefits

• Two-Stage Distillation: Combines CFG distillation with SCFM for maximum efficiency—the SCFM was trained on top of the already CFG-distilled merged model.
• Few-Step Generation: SCFM enables efficient sampling in significantly fewer inference steps.
• No CFG Overhead: Running at guidance_scale=1 means calculating the noise prediction only once per step instead of twice.
• Quality Tradeoff: As a distillation approach, there is a slight quality degradation compared to the full model at CFG=5, but the speed gains make it ideal for rapid iteration and production workflows.
• Drop-in Replacement: Works seamlessly with existing FIBO workflows—just set guidance_scale=1.0.
• Memory Efficient: Minimal additional GPU memory overhead.