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Model quantization v1.0.0

Use this resource to reduce the size of a model through quantization

New

  • 452 downloads
  • 196 likes
  • 103 saves

Free

Install with the CLI

In a terminal, from the folder you want:

npx --yes palatekit@latest install model-quantization

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 chooses the quantization level, applies the conversion and compares quality before and after. You get the reduced model and a comparison table.

Mostly picked by

Updated November 2, 2026

Card for the “Model quantization” skill

Details

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

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What you get

  • SKILL.md: quantization method and checkpoints
  • SKILL.md: command examples and expected output

Good fit for

  • Your model does not fit on the target hardware
  • Inference cost is too high for your traffic

Not for

    Tags

    • quantization
    • inference
    • optimization
    • model

    About

    You say

    “Quantize my model to int8 so it runs on a server without GPU, and compare the accuracy.”

    Card for the “Model quantization” 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 reduce the size of a model through quantization
    3. Review and adjust the result

    Content preview

    Files

    • LICENSE1.1 KB
    • NOTICE-PALATEKIT.md0.6 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/model-quantization-tool
    Licence
    MIT

    Notice

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

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