vastai-deploy-integration
Deploy ML training jobs and inference services on Vast.ai GPU cloud. Use when deploying GPU workloads, configuring Docker images, or setting up automated deployment scripts. Trigger with phrases like "deploy vastai", "vastai deployment", "vastai docker", "vastai production deploy". '
npx skills add jeremylongshore/claude-code-plugins-plus-skills --skill vastai-deploy-integration --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.
# Vast.ai Deploy Integration ## Overview Deploy ML training jobs and inference services on Vast.ai GPU cloud. Covers Docker image optimization, automated provisioning scripts, data transfer strategies, and deployment automation. ## Prerequisites - Vast.ai CLI authenticated - Docker image published to a registry - Training/inference code tested locally ## Instructions ### Step 1: Optimized Docker I
What does the vastai-deploy-integration skill do?
Deploy ML training jobs and inference services on Vast.ai GPU cloud. Use when deploying GPU workloads, configuring Docker images, or setting up automated deployment scripts. Trigger with phrases like "deploy vastai", "vastai deployment", "vastai docker", "vastai production deploy". '
How do I install it?
Run `npx skills add jeremylongshore/claude-code-plugins-plus-skills --skill vastai-deploy-integration --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.
