AlibabaResearch/SparkDiffusion

Generative mediaPython

1.3 Early signal Magnitude out of 10 — how fast interest is growing, not a quality score. Star growth looks organic. Data as of September 24, 2026, 02:50 UTC.

Open on Seismograph Open on GitHub

About the project

A video-generation acceleration framework for Diffusion Transformer models, combining sparse low-rank attention (RoLa), few-step distillation (CrossDistill) and custom operators to deliver 200×+ inference speedups for Wan 2.1/2.2.

Useful for

Speed up Wan 2.1/2.2 inference via sparse finetuning and distillation
Finetune a DiT model with RoLa sparse attention on a custom dataset
Run single-case T2V or I2V generation through the provided scripts

README summarized by DeepSeek V4.1 Flash. Details may be inaccurate.

Why it’s trending

0 stars so far today, about 4 expected by the end of the day.
The repository is 6 days old and already has 89 stars. With less than two weeks of history, there's no usual pace to compare the spike against yet.
Top new repositories this week: #185.

Stars per day

Bars are daily stars, the line is the usual pace. Red marks spike days.

Numbers

Total stars: 89
Today: 0 · ≈ 4 by evening
Forks: 2
Issues and pull requests: 1
Watchers: 1
Language: Python
License: Apache-2.0
Created: September 18, 2026
Last push: September 23, 2026

Star trust

Growth looks organic: forks and discussion are in line with active projects, and stars arrive unevenly, the way people give them.

These are heuristics, not a verdict: we judge by the repository’s behavior, not by a list of stargazers.

Spotted in

September 24, 2026Top new repositories this week: #184

README badge

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