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Deploying machine learning models to production v1.0.0

Use this resource to deploy a machine learning model and monitor it in production

New

  • 417 downloads
  • 152 likes
  • 215 saves

Free

Install with the CLI

In a terminal, from the folder you want:

npx --yes palatekit@latest install production-ml-model-serving

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 designs the inference service, prepares features, optimises inference, then sets up A/B tests and monitoring. It draws on PyTorch 2.x, TensorFlow and common ML deployment tools.

Mostly picked by

Updated November 2, 2026

Card for the “Deploying machine learning models to production” skill

Details

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

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What you get

  • SKILL.md: ML frameworks, model serving and deployment
  • SKILL.md: feature engineering, training, infrastructure and MLOps

Good fit for

  • You must serve a model behind a low-latency API
  • You want to run A/B tests on a model

Not for

    Tags

    • machine learning
    • inference
    • pytorch
    • mlops

    About

    You say

    “Deploy this PyTorch model behind an inference API, with monitoring and A/B tests.”

    Card for the “Deploying machine learning models to production” skill

    Skill published by rmyndharis 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 deploy a machine learning model and monitor it in production
    3. Review and adjust the result

    Content preview

    Files

    • LICENSE1 KB
    • NOTICE-PALATEKIT.md0.5 KB
    • SKILL.md9.2 KB

    Origin and licence

    Listed unmodified

    Author
    rmyndharis
    Source
    github.com/rmyndharis/antigravity-skills/tree/364ea63c190fcf7cac035f7fa91f0406fa392584/skills/ml-engineer
    Licence
    MIT

    Notice

    « ml-engineer » (rmyndharis, MIT) livré dans sa version d'origine : fiche en français et en anglais par PalateKit.

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