gguf-quantization
GGUF format and llama.cpp quantization for efficient CPU/GPU inference. Use when deploying models on consumer hardware, Apple Silicon, or when needing flexible quantization from 2-8 bit without GPU requirements.
- Skills
- AI research
- 2
What it does and how to use it
A skill that teaches Claude Code to do ai research tasks well. It is packaged knowledge the model uses whenever it is relevant.
- Install the skill (command above).
- In Claude Code, describe what you need - the skill turns on by itself when the context fits.
- No commands to memorize: you talk in plain language and the skill does the rest.
Install (Claude Code)
mkdir -p .claude/skills/gguf-quantization && curl -fsSL https://doutorai.pt/data/lib/skills__gguf-quantization.md -o .claude/skills/gguf-quantization/SKILL.mdPaste this command into the terminal, in your project folder, and the component installs automatically.
Content
---
name: gguf-quantization
description: GGUF format and llama.cpp quantization for efficient CPU/GPU inference. Use when deploying models on consumer hardware, Apple Silicon, or when needing flexible quantization from 2-8 bit without GPU requirements.
version: 1.0.0
author: Orchestra Research
license: MIT
tags: [GGUF, Quantization, llama.cpp, CPU Inference, Apple Silicon, Model Compression, Optimization]
dependencies: [llama-cpp-python>=0.2.0]
---
# GGUF - Quantization Format for llama.cpp
The GGUF (GPT-Generated Unified Format) is the standard file format for llama.cpp, enabling efficient
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