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Running a model locally with GGUF and llama.cpp v1.0.0

Use this resource to convert and quantize a model to GGUF for local inference

New

  • 381 downloads
  • 229 likes
  • 117 saves

Free

Install with the CLI

In a terminal, from the folder you want:

npx --yes palatekit@latest install gguf-llama-cpp-quantization-2

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 building llama.cpp (CPU, CUDA or Metal), converting a Hugging Face model to GGUF, then quantizing it from 2 to 8 bits. You get build and conversion commands suited to your hardware.

Mostly picked by

Updated November 2, 2026

Card for the “Running a model locally with GGUF and llama.cpp” skill

Details

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

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What you get

  • SKILL.md: building llama.cpp and converting the model
  • references/advanced-usage.md and troubleshooting.md: advanced quantization and troubleshooting

Good fit for

  • You want to run a model on a laptop or a Mac
  • You use LM Studio or Ollama and want a compatible format

Not for

    Tags

    • gguf
    • llama.cpp
    • quantization
    • local

    About

    You say

    “Convert this Hugging Face model to GGUF Q4 so I can run it on my M2 Mac.”

    Card for the “Running a model locally with GGUF and llama.cpp” skill

    Skill published by Orchestra Research 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 convert and quantize a model to GGUF for local inference
    3. Review and adjust the result

    Content preview

    Files

    • LICENSE1.1 KB
    • NOTICE-PALATEKIT.md0.5 KB
    • references/advanced-usage.md11.1 KB
    • references/troubleshooting.md9.1 KB
    • SKILL.md10.5 KB

    Origin and licence

    Listed unmodified

    Author
    Orchestra Research
    Source
    github.com/orchestra-research/ai-research-skills/tree/773a52944ba4747a18bd4ae9ade53fff041adcbc/10-optimization/gguf
    Licence
    MIT

    Notice

    « gguf-quantization » (Orchestra Research, MIT) livré dans sa version d'origine : fiche en français et en anglais par PalateKit.

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