distributed-training-setup
Configure distributed training setup operations. Auto-activating skill for ML Training. Triggers on: distributed training setup, distributed training setup Part of the ML Training skill category. Use when working with distributed training setup functionality. Trigger with phrases like "distributed training setup", "distributed setup", "distributed". '
npx skills add jeremylongshore/claude-code-plugins-plus-skills --skill distributed-training-setup --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Distributed Training Setup ## Overview This skill provides automated assistance for distributed training setup tasks within the ML Training domain. ## When to Use This skill activates automatically when you: - Mention "distributed training setup" in your request - Ask about distributed training setup patterns or best practices - Need help with machine learning training skills covering data prepa
What does the distributed-training-setup skill do?
Configure distributed training setup operations. Auto-activating skill for ML Training. Triggers on: distributed training setup, distributed training setup Part of the ML Training skill category. Use when working with distributed training setup functionality. Trigger with phrases like "distributed training setup", "distributed setup", "distributed". '
How do I install it?
Run `npx skills add jeremylongshore/claude-code-plugins-plus-skills --skill distributed-training-setup --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From jeremylongshore/claude-code-plugins-plus-skills, a repository with 2,596 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.