Summary
If you're working with transformer models and attention is your bottleneck, this implements Flash Attention to speed things up 2-4x while cutting memory usage by 10-20x. It uses IO-aware tiling and recomputation tricks under the hood. The skill shows you how to use PyTorch's native scaled_dot_product_attention (which auto-detects Flash Attention support) plus presumably the standalone flash-attn library for more control. Worth noting this has passed multiple security audits and comes from a repo with solid GitHub traction. The performance gains are real and measurable, especially on longer sequences where standard attention becomes prohibitively expensive.
Install to Claude Code
npx -y skills add orchestra-research/ai-research-skills --skill optimizing-attention-flash --agent claude-codeInstalls into .claude/skills of the current project.
Keep your Mac awake while Claude Code and 40+ AI agents run. Sleeps when they're idle.
One time payment $9 →
Integrate web data into your AI product. One API to scrape website & brand data.
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Agent, run crypto. Access onchain data & trade routes via 1inch.
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On Capafy, your Skill runs online 24/7 as an agent product, and you get paid every time someone uses it.
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Files
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Featured
Keep your Mac awake while Claude Code and 40+ AI agents run. Sleeps when they're idle.
One time payment $9 →Integrate web data into your AI product. One API to scrape website & brand data.
Get API Key Now →Agent, run crypto. Access onchain data & trade routes via 1inch.
Install now →On Capafy, your Skill runs online 24/7 as an agent product, and you get paid every time someone uses it.
Start earning →
