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Tracking ML experiments and optimizing with Weights & Biases v1.0.0

Use this resource to track experiments, compare runs and launch hyperparameter sweeps

New

  • 579 downloads
  • 156 likes
  • 232 saves

Free

Install with the CLI

In a terminal, from the folder you want:

npx --yes palatekit@latest install wandb-experiment-tracking-sweeps

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 helps you install W&B, log in, initialize a run in your training loop and log metrics. It also covers hyperparameter sweeps, artifacts and the model registry.

Mostly picked by

Updated November 2, 2026

Card for the “Tracking ML experiments and optimizing with Weights & Biases” skill

Details

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

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What you get

  • SKILL.md: installation, login, run and PyTorch integration
  • references/sweeps.md, artifacts.md and integrations.md: sweeps, artifacts and integrations

Good fit for

  • You want to share your curves with a team
  • You look for the best hyperparameters with an automatic sweep

Not for

    Tags

    • tracking
    • hyperparameters
    • mlops
    • team

    About

    You say

    “Add W&B to my training and launch a sweep over learning rate and batch size.”

    Card for the “Tracking ML experiments and optimizing with Weights & Biases” skill

    Skill published by Orchestra Research 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 track experiments, compare runs and launch hyperparameter sweeps
    3. Review and adjust the result

    Content preview

    Files

    • LICENSE1.1 KB
    • NOTICE-PALATEKIT.md0.5 KB
    • references/artifacts.md13.7 KB
    • references/integrations.md16.5 KB
    • references/sweeps.md18.1 KB
    • SKILL.md12.7 KB

    Origin and licence

    Listed unmodified

    Author
    Orchestra Research
    Source
    github.com/orchestra-research/ai-research-skills/tree/773a52944ba4747a18bd4ae9ade53fff041adcbc/13-mlops/weights-and-biases
    Licence
    MIT

    Notice

    « weights-and-biases » (Orchestra Research, MIT) livré dans sa version d'origine : fiche en français et en anglais par PalateKit.

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