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SageMaker endpoint deployment v1.0.0

Use this resource to deploy a model to a SageMaker endpoint

New

  • 491 downloads
  • 178 likes
  • 182 saves

Free

Install with the CLI

In a terminal, from the folder you want:

npx --yes palatekit@latest install sagemaker-endpoint-deployment

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 guides you through deploying a machine learning model to a SageMaker endpoint. You get a step-by-step method with prerequisites, examples and error handling.

Mostly picked by

Updated November 2, 2026

Card for the “SageMaker endpoint deployment” skill

Details

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

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What you get

  • SKILL.md: deployment steps and best practices
  • SKILL.md: prerequisites, examples and error handling

Good fit for

  • You need to serve a trained model through an API
  • An existing SageMaker endpoint needs an update

Not for

    Tags

    • sagemaker
    • machine learning
    • deployment
    • aws

    About

    You say

    “Deploy my trained model to a SageMaker endpoint on a ml.m5.large instance in eu-west-1.”

    Card for the “SageMaker endpoint deployment” skill

    Skill published by Jeremy Longshore <jeremy@intentsolutions.io> 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 model to a SageMaker endpoint
    3. Review and adjust the result

    Content preview

    Files

    • LICENSE1.1 KB
    • NOTICE-PALATEKIT.md0.6 KB
    • SKILL.md2.4 KB

    Origin and licence

    Listed unmodified

    Author
    Jeremy Longshore <jeremy@intentsolutions.io>
    Source
    github.com/jeremylongshore/tons-of-skills-marketplace/tree/ab85a061f7bcc039dac13ee193de7a4cd4388571/skills/08-ml-deployment/sagemaker-endpoint-deployer
    Licence
    MIT

    Notice

    « sagemaker-endpoint-deployer » (Jeremy Longshore <jeremy@intentsolutions.io>, MIT) livré dans sa version d'origine : fiche en français et en anglais par PalateKit.

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