Summary
If you're scaling PyTorch or TensorFlow training beyond a single machine, this handles the distributed orchestration without rewriting your code. Wrap your training function, specify worker count, and Ray manages GPU allocation, fault tolerance, and metric aggregation across nodes. The real win is tight integration with Ray Tune for distributed hyperparameter sweeps. Setup is genuinely simpler than raw PyTorch DDP or Horovod, though you're buying into the Ray ecosystem. Works well for large model training or running dozens of experiments in parallel across a cluster.
Install to Claude Code
npx -y skills add orchestra-research/ai-research-skills --skill ray-train --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.
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 →
Files
SKILL.md
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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 →
