distributed-training

Use when training models across multiple GPUs or nodes, handling large models that don't fit in memory, or optimizing training throughput - covers DDP, FSDP, DeepSpeed ZeRO, model/data parallelism, and gradient checkpointingUse when ", " mentioned.

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Repository: omer-metin/skills-for-antigravity
Last source activity: January 22, 2026 at 14:14
Detected SKILL.md language: English
Stars: 128
Forks: 24

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3d-web-experience

Expert in building 3D experiences for the web - Three.js, React Three Fiber, Spline, WebGL, and interactive 3D scenes. Covers product configurators, 3D portfolios, immersive websites, and bringing depth to web experiences. Use when "3D website, three.js, WebGL, react three fiber, 3D experience, spline, product configurator, " mentioned.

2026-01-22

a-b-testing

The science of learning through controlled experimentation. A/B testing isn't about picking winners—it's about building a culture of validated learning and reducing the cost of being wrong. This skill covers experiment design, statistical rigor, feature flagging, analysis, and building experimentation into product development. The best experimenters know that every test, positive or negative, teaches something valuable. Use when "a/b test, experiment, hypothesis, statistical significance, sample size, feature flag, variant, control, treatment, p-value, conversion rate, test winner, split test, experimentation, testing, statistics, feature-flags, hypothesis, growth, optimization, learning, validation" mentioned.

2026-01-22

absurdist-voice

Expert in absurdist, unhinged, and deliberately weird brand voices that work. Covers the Duolingo owl energy, chaotic social media presence, and knowing exactly how far to push. Understands why weird works and when it catastrophically fails. Use when "absurdist, unhinged, duolingo, weird brand, chaotic energy, off the rails, brand character, " mentioned.

2026-01-22

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name	distributed-training
description	Use when training models across multiple GPUs or nodes, handling large models that don't fit in memory, or optimizing training throughput - covers DDP, FSDP, DeepSpeed ZeRO, model/data parallelism, and gradient checkpointingUse when ", " mentioned.