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Distributed training and hyperparameter search with Ray v1.0.0

Use this resource to run distributed training across several machines with Ray

New

  • 485 downloads
  • 140 likes
  • 237 saves

Free

Install with the CLI

In a terminal, from the folder you want:

npx --yes palatekit@latest install ray-train-distributed-training

With no option, the skill goes to ~/.agents/skills/; add --agent claude-code (or codex, cursor…) to target an agent.

First time: connect the CLI with

npx --yes palatekit@latest login

The agent adapts your training function to Ray Train, sets the number of workers and, if needed, a hyperparameter search with Ray Tune and early stopping. You get the launch script and its multi-node configuration.

Mostly picked by

Updated November 2, 2026

Card for the “Distributed training and hyperparameter search with Ray” skill

Details

Works in
Install guides
Generates with
Your agent's model
Licence
MIT

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What you get

  • SKILL.md: quick start and three workflows (PyTorch, Transformers, Ray Tune)
  • references/multi-node.md: setup for training across several machines

Good fit for

  • You want to scale your PyTorch code to eight GPUs without rewriting it
  • You run many hyperparameter trials in parallel

Not for

    Tags

    • ray
    • distributed training
    • ray tune
    • hyperparameters

    About

    You say

    “Adapt my PyTorch script to Ray Train on 2 nodes of 8 GPUs and run 20 trials with early stopping.”

    Card for the “Distributed training and hyperparameter search with Ray” skill

    Skill published by davila7 under the MIT license, delivered in its original version.

    Show more

    How to use it

    1. Install the skill in your agent's skills folder
    2. Ask your agent to run distributed training across several machines with Ray
    3. Review and adjust the result

    Content preview

    Files

    • LICENSE1.1 KB
    • NOTICE-PALATEKIT.md0.5 KB
    • references/multi-node.md13.8 KB
    • SKILL.md10.9 KB

    Origin and licence

    Listed unmodified

    Author
    davila7
    Source
    github.com/davila7/claude-code-templates/tree/f57964ebda91cdfb31755661ecea9395f30020f1/cli-tool/components/skills/ai-research/distributed-training-ray-train
    Licence
    MIT

    Notice

    « distributed-training-ray-train » (davila7, MIT) livré dans sa version d'origine : fiche en français et en anglais par PalateKit.

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