Every premium and members-only resource for $9.99/month, as a no-commitment subscription. See the plans

PalateKit

Sign in
Menu

Request a resource

Describe the resource you are missing in one sentence. We will email you when it is published.

0 / 280

A page, a video or an image online.

Unlock PalateKit

Unlock everything

Plan

Paying means accepting our terms of sale.

Secure payment by Stripe. Receipts and invoices sent by email.

Welcome back

Sign in to install, download or save this resource. A free account is enough for free resources.

Tune GPU usage in deployment v1.0.0

Use this resource to tune GPU usage for serving models in production

New

  • 314 downloads
  • 121 likes
  • 155 saves

Free

Install with the CLI

In a terminal, from the folder you want:

npx --yes palatekit@latest install gpu-inference-resource-tuning

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 walks you through sharing GPU resources across served models, adjusting batch sizes and tracking utilization. You get settings to measure before and after each change.

Mostly picked by

Updated November 2, 2026

Card for the “Tune GPU usage in deployment” skill

Details

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

Similar resources

View all

What you get

  • SKILL.md: tuning steps and examples
  • SKILL.md: prerequisites, expected outputs and common errors

Good fit for

  • Your GPUs are underused or saturated in production
  • You serve several models on one machine

Not for

    Tags

    • gpu
    • inference
    • optimization
    • deployment
    • resources

    About

    You say

    “My inference service saturates the GPU, help me tune batch sizes and allocation.”

    Card for the “Tune GPU usage in 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 tune GPU usage for serving models in production
    3. Review and adjust the result

    Content preview

    Files

    • LICENSE1.1 KB
    • NOTICE-PALATEKIT.md0.5 KB
    • SKILL.md2.3 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/gpu-resource-optimizer
    Licence
    MIT

    Notice

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

    User reviews

    –

    No ratings yet

    Loading reviews…

    Delete your review?

    Your rating and comment will be removed from the page.