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Commits, branches and sync with the but CLI
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- Codex
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llama.cpp: LLM inference on CPU and Apple Silicon v1.0.0
Use this resource to run an LLM locally on CPU, Apple Silicon or non-NVIDIA GPUs with llama.cpp
New
- 315 downloads
- 147 likes
- 174 saves
Free
Install with the CLI
In a terminal, from the folder you want:
npx --yes palatekit@latest install llama-cpp-local-inferenceWith 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 loginThe agent installs llama.cpp for your hardware (Metal, CUDA, ROCm or CPU), downloads a GGUF model, chooses the quantization and starts a local server. You get inference without Docker or Python, suited to edge deployment.
Mostly picked by
Updated November 2, 2026
Previews
Details
- Install guides
- Generates with
- Your agent's model
- Licence
- MIT
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What you get
- SKILL.md: installation, model download and launch
- references/quantization.md: GGUF formats and quantization trade-offs
- references/server.md: server configuration
Good fit for
- You want to run a model on an M1 to M4 Mac
- You deploy to a machine without an NVIDIA GPU
Not for
Tags
- llama.cpp
- gguf
- local inference
About
You say
“Install llama.cpp with Metal on my Mac and run a 4-bit quantized GGUF model.”
Skill published by davila7 under the MIT license, delivered in its original version.
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How to use it
- Install the skill in your agent's skills folder
- Ask your agent to run an LLM locally on CPU, Apple Silicon or non-NVIDIA GPUs with llama.cpp
- Review and adjust the result
Content preview
Files
- LICENSE1.1 KB
- NOTICE-PALATEKIT.md0.5 KB
- references/optimization.md1.7 KB
- references/quantization.md5 KB
- references/server.md2.3 KB
- SKILL.md6.1 KB
Origin and licence
Listed unmodified
- Author
- davila7
- Source
- github.com/davila7/claude-code-templates/tree/f57964ebda91cdfb31755661ecea9395f30020f1/cli-tool/components/skills/ai-research/inference-serving-llama-cpp
- Licence
- MIT
Notice
« inference-serving-llama-cpp » (davila7, MIT) livré dans sa version d'origine : fiche en français et en anglais par PalateKit.
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