ray-train
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.
Install
npx skills add davila7/claude-code-templates@ray-trainRuns in your terminal. Adds the skill globally for Claude Code, Cursor, Codex and others; add -g -y to skip prompts.
What it does
Ray Train - Distributed Training Orchestration Quick start Ray Train scales machine learning training from single GPU to multi-node clusters with minimal code changes. Installation: Basic PyTorch training (single node): That's it! Ray handles: - Distributed coordination - GPU allocation - Fault tolerance - Checkpointing - Metric aggregation Common workflows Workflow 1: Scale existing PyTorch code Original single-GPU code: Ray Train version (scales to multi-GPU/multi-node): Benefits: Same code runs on 1 GPU or 1000 GPUs Workflow 2: HuggingFace Transformers integration Workflow 3:…
Excerpt from the skill's own SKILL.md. Read the full file on GitHub before installing: skills run with your agent's permissions.
View source on GitHubBefore you install
Skills are plain text instructions the agent follows, sometimes with scripts. Check the source, prefer repositories with many installs and stars, and read any script it ships.
Categories
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