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llama-cpp

Execute local GGUF inference with llama.cpp and Hugging Face Hub model discovery.

1|Updated Feb 17, 2026
Search Tags:#GGUF#inference#model discovery#Hugging Face Hub#llama.cpp
One-click install
npx skills add https://github.com/brittaniebuffiecsu/zerogravityclaw --skill llama-cpp-brittaniebuffiecsu
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: llama-cpp
Source: https://github.com/brittaniebuffiecsu/zerogravityclaw/tree/main/src/hermes-core/skills/mlops/inference/llama-cpp
Command: npx skills add https://github.com/brittaniebuffiecsu/zerogravityclaw --skill llama-cpp-brittaniebuffiecsu

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires llama-cpp-python>=0.2.0, and includes scripts (resource) and references (resource) and assets (resource) components.

What problem does it solve?

This Skill provides a comprehensive solution for local GGUF inference, quant selection, and Hugging Face Hub model discovery using llama.cpp.

Core Features & Use Cases

  • Local GGUF Inference: Run llama.cpp on local systems for CPU, Apple Silicon, CUDA, ROCm, or Intel GPUs.
  • Model Discovery: Search and explore Hugging Face Hub for llama.cpp compatible models.
  • Quick Start: Use the skill to run a specific model from the Hub, e.g., 'llama-server -hf bartowski/Llama-3.2-3B-Instruct-GGUF:Q8_0'.

Quick Start

Run the llama.cpp inference server for the model 'bartowski/Llama-3.2-3B-Instruct-GGUF:Q8_0' on the local system.

Frequently Asked Questions about llama-cpp

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I run local GGUF inference using llama.cpp?▼

Run local GGUF inference by executing llama.cpp via Python bindings on your system, specifying the model and quantization for CPU, Apple Silicon, CUDA, ROCm, or Intel GPUs.

How do I discover llama.cpp compatible models on Hugging Face Hub?▼

Discover llama.cpp compatible models on Hugging Face Hub by using the Skill's model discovery feature to search and explore available GGUF repositories.

Does llama.cpp Python support inference on Apple Silicon and CUDA GPUs?▼

llama.cpp Python supports local inference across CPU, Apple Silicon, CUDA, ROCm, and Intel GPUs, allowing flexible hardware acceleration for GGUF models.

What is the best way to select a quantization level for a Hugging Face GGUF model?▼

Select a GGUF quantization level by specifying the desired format, such as Q8_0, when fetching the model from Hugging Face Hub to balance inference speed and memory.

How do I start the llama-server with a specific GGUF model?▼

Start the llama-server by executing a command like 'llama-server -hf bartowski/Llama-3.2-3B-Instruct-GGUF:Q8_0' to run the specified Hugging Face Hub model locally.

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