Search Results for "command line"

...This approach reduces active memory use to roughly 2 GB while the installed model occupies about 14.3 GB of storage. The project includes a native Mac application, command-line tools, a streaming installer, a Swift library, and an experimental OpenAI-compatible local server. Quantized weights, custom Metal kernels, chunked prefill, and a bounded expert cache improve efficiency. The installer downloads and repacks model ranges without staging a second full checkpoint. Its current scope is text-only Gemma inference on macOS 26 and Apple Silicon hardware.

...It can provide controlled access to Calendar, Contacts, Location, Maps, Messages, Reminders, and Weather. The menu bar interface lets users enable individual services and approve the required macOS permissions. A bundled command-line server communicates over standard input and output with clients such as Claude Desktop, Claude Code, Cursor, and Amp. Calendar and reminder tools can create items, while other tools support searches, directions, travel estimates, message history, and current conditions. The app itself does not collect or store user data, although connected AI clients may send tool results off device. ...

apfel is a lightweight and likely experimental development project focused on building efficient and minimal tools or frameworks, typically emphasizing simplicity, performance, and clean abstractions. The project appears to follow a philosophy of reducing unnecessary complexity while still enabling practical functionality for developers who prefer lean systems over heavy frameworks. It is designed to be adaptable, allowing developers to extend or modify its behavior depending on their...

Ollamac is an open-source native macOS application that provides a graphical interface for interacting with local large language models running through the Ollama inference framework. The project was created to simplify the process of using local AI models, which typically require command-line interaction, by offering a clean and intuitive desktop interface. Through this interface, users can run and chat with a variety of LLM models installed through Ollama directly on their own machines. The application focuses on delivering a lightweight and responsive experience that integrates seamlessly with the macOS ecosystem. ...