lvsa-tuning

What problem does it solve?

LVSA tuning helps ML practitioners optimize the long-video sparse attention scheduler to achieve a desired balance between visual quality and generation speed, without changing model weights.

Core Features & Use Cases

• Knob-based optimization: adjust sparsity_scale, window_size, and n_first_frames to control long-range attention budget.
• Rotation and extrapolation: enable rotate-keyframes and RIFLEx composition to extend horizon without quality collapse.
• Practical guidance: choose configurations for Wan, HunyuanVideo, or CogVideo-like models to meet latency targets while preserving motion fidelity.

Quick Start

Tune LVSA by adjusting sparsity_scale and window settings to achieve the desired balance between quality and speed for your Wan/HunyuanVideo experiments.