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4-bit LLM quantization with GPTQ v1.0.0

Use this resource to quantize an LLM to 4 bits after training with GPTQ

New

  • 359 downloads
  • 118 likes
  • 237 saves

Free

Install with the CLI

In a terminal, from the folder you want:

npx --yes palatekit@latest install gptq-4bit-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 installs AutoGPTQ, loads a quantized model or calibrates your own, then connects it to Transformers and PEFT for QLoRA fine-tuning. You get a lighter model and guidance on calibration.

Mostly picked by

Updated November 2, 2026

Card for the “4-bit LLM quantization with GPTQ” skill

Details

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

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What you get

  • SKILL.md: installing AutoGPTQ, loading and generation
  • references/calibration.md: calibrating and quantizing your model
  • references/integration.md: integration with Transformers and PEFT

Good fit for

  • A 70-billion-parameter model must fit on consumer GPUs
  • You want QLoRA fine-tuning on a quantized model

Not for

    Tags

    • gptq
    • quantization
    • calibration
    • llm

    About

    You say

    “Quantize our model to 4-bit GPTQ with a representative calibration set, then measure perplexity.”

    Card for the “4-bit LLM quantization with GPTQ” skill

    Skill published by davila7 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 quantize an LLM to 4 bits after training with GPTQ
    3. Review and adjust the result

    Content preview

    Files

    • LICENSE1.1 KB
    • NOTICE-PALATEKIT.md0.5 KB
    • references/calibration.md8.3 KB
    • references/integration.md2.9 KB
    • references/troubleshooting.md1.9 KB
    • SKILL.md11.8 KB

    Origin and licence

    Listed unmodified

    Author
    davila7
    Source
    github.com/davila7/claude-code-templates/tree/f57964ebda91cdfb31755661ecea9395f30020f1/cli-tool/components/skills/ai-research/optimization-gptq
    Licence
    MIT

    Notice

    « optimization-gptq » (davila7, MIT) livré dans sa version d'origine : fiche en français et en anglais par PalateKit.

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