CLI Tools for AI

CLI Tools for AI

Running AI models locally does not require a fancy graphical interface. Some of the most powerful and flexible tools are command line utilities. These tools give you full control over how models run, and they are often more efficient than their graphical counterparts.

Ollama is the most popular tool for running models locally. It provides a simple command line interface for downloading, running, and managing models. With commands like ollama run llama3, you can start chatting with a model in seconds. Ollama handles model downloading, quantization, and GPU acceleration automatically. It also provides a compatible API so you can use it with any OpenAI compatible client.

llama.cpp is the engine that powers many local AI tools, including Ollama. It is a C++ implementation of the Llama architecture that is highly optimized for CPU and GPU inference. llama.cpp introduced the GGUF format, which has become the standard for quantized models. You can use llama.cpp directly for maximum control, or use higher level tools built on top of it.

Text Generation WebUI, also known as Oobabooga, provides a browser based interface for running models. While it is not a CLI tool itself, it is often used alongside CLI tools for management. It supports multiple model backends, including llama.cpp and ExLlama, and offers features like chat mode, instruction following, and parameter tuning through a web interface.

Other useful CLI tools include LM Studio for model discovery and testing, llamafile for running models as single executable files, and vLLM for high performance inference servers. The ecosystem of local AI tools is growing rapidly, and most of them are open source, free, and designed to work with consumer hardware. This makes local AI accessible to anyone willing to use a terminal.