Overview
ray-train is an open-source workflow skill for Claude Code and compatible agents, published by Orchestra-Research. Its author describes it as: “Distributed training orchestration across clusters. Scales PyTorch/TensorFlow/HuggingFace from laptop to 1000s of nodes. Built-in hyperparameter tuning with Ray Tune, fault tolerance, elastic scaling. Use when trainin…”. The project has 12k stars on GitHub and is available under the MIT license. Add it to your setup with `/plugin marketplace add Orchestra-Research/AI-Research-SKILLs`.
What ray-train does
Ray Train scales machine learning training from single GPU to multi-node clusters with minimal code changes.
What’s inside
The SKILL.md for ray-train is organised into these sections:
- Quick start
- Common workflows
- Workflow 1: Scale existing PyTorch code
- Workflow 2: HuggingFace Transformers integration
- Workflow 3: Hyperparameter tuning with Ray Tune
- Workflow 4: Checkpointing and fault tolerance
- Workflow 5: Multi-node training
- When to use vs alternatives
- Common issues
- Advanced topics
- Hardware requirements
- Resources
Installation
Add ray-train to your agent with:
/plugin marketplace add Orchestra-Research/AI-Research-SKILLsReview a skill’s source before installing it — skills can instruct your agent to run commands. This command comes from the skill’s public repository, which is the source of truth for setup steps. New to skills? Read how to install Claude Code skills.
Supported agents
- Claude Code — ships a claude code plugin marketplace
- Codex — declared in the repository topics
License
ray-train is published under the MIT license.
Strengths
- Clear MIT license — safe to read and adapt within its terms
- Ships in Orchestra-Research/AI-Research-SKILLs, an established project with 11,807 GitHub stars
- Works with Claude Code, Codex
Author
Topics
Frequently asked questions
- What does ray-train do?
- Distributed training orchestration across clusters. Scales PyTorch/TensorFlow/HuggingFace from laptop to 1000s of nodes. Built-in hyperparameter tuning with Ray Tune, fault tolerance, elastic scaling. Use when training massive models across multiple machines or running distributed hyperparameter sweeps.
- How do I install ray-train?
- Run /plugin marketplace add Orchestra-Research/AI-Research-SKILLs in your agent, then reload your skills. Review the source at https://github.com/Orchestra-Research/AI-Research-SKILLs before installing.
- Is ray-train free to use?
- Yes. ray-train is free and open source under the MIT license, so you can read, run, and adapt it within that license's terms.
- Which agents does ray-train work with?
- ray-train lists Claude Code and Codex — named in its SKILL.md, its plugin marketplace or its repository topics. Skills use the portable SKILL.md format, so other agents that read that format may load it too.
- Where does ray-train come from?
- ray-train ships inside Orchestra-Research/AI-Research-SKILLs, a repository that contains 41 catalogued skills in total. The repository's 11,807 GitHub stars apply to that whole collection, not to this skill on its own.