GGML 基礎入門介紹：讓大語言模型在消費級硬體上高效運行的關鍵技術
Original: Introduction to ggml
GGML is a lightweight, zero-dependency C/C++ tensor library developed by Georgi Gerganov. It was originally designed to enable efficient…
本篇 Hugging Face 部落格文章深入介紹了由 Georgi Gerganov 開發的輕量級 C/C++ 張量庫 GGML。GGML 是 llama.cpp 的底層核心，專為消費級硬體（如 CPU 和 Apple Silicon）優化。文章解析了其無依賴性、高效量化（4-bit/8-bit）以及如何演進至現今主流的 GGUF 格式，是理解本地端 LLM 部署的必讀指南。
GGML is a lightweight, zero-dependency C/C++ tensor library developed by Georgi Gerganov. It was originally designed to enable efficient local inference of the Whisper speech recognition model (whisper.cpp), and was later applied to local deployment of Llama models (llama.cpp), sparking a revolution in the open-source AI community around running large language models (LLMs) locally.
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