Running LLMs Locally on macOS: A Skeptic's Guide
This blog post details the author's experience running large language models (LLMs) locally on their macOS machine. While expressing skepticism about the hype surrounding LLMs, the author provides a practical guide to installing and using tools like llama.cpp and LM Studio. The guide covers choosing appropriate models based on factors like size, runtime, quantization, and reasoning capabilities. The author emphasizes the privacy benefits and reduced reliance on AI companies that come with local LLM deployment, offering tips and tricks such as utilizing MCPs to extend functionality and managing the context window to prevent information loss. The post also touches on the ethical concerns surrounding the current state of the AI industry.
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