{"repo":"Mcourtyard/m-courtyard","free":true,"listed":false,"github":"https://github.com/Mcourtyard/m-courtyard","clone":"git clone https://github.com/Mcourtyard/m-courtyard.git","description":"M-Courtyard: Local AI Model Fine-tuning Assistant for Apple Silicon. Zero-code, zero-cloud, privacy-first desktop app powered by Tauri + React + mlx-lm.","language":"TypeScript","stars":163,"topics":["ai-assistant","apple-silicon","desktop-app","fine-tuning","llm","local-llm","lora","macos","mlx","ollama"],"license":null,"category":"ai-agents","readme_excerpt":"# M-Courtyard Zero-code local LLM fine-tuning & data prep on Apple Silicon. Privacy-first, powered by MLX. English 简体中文 --- Why M-Courtyard? M-Courtyard is a desktop assistant designed to demystify LLM fine-tuning. Forget about writing Python scripts, managing CUDA dependencies, or renting expensive cloud GPUs. If you have an Apple Silicon Mac, you can build your own custom AI locally. - Zero-Code Pipeline : From raw PDF/DOCX files to local datasets, MLX fine-tuning, and exportable local runtimes in 4 easy steps. - 100% Local & Private : No data leaves your machine. Perfect for fine-tuning on sensitive enterprise data or personal journals. - Optimized for Apple MLX : Powered by mlx-lm , maximizing the potential of unified memory on M1/M2/M3/M4 chips. - AI-Powered Data Prep : Automatically turn unstructured documents into high-quality instruction datasets using local models, or fall back to built-in rules when you do not want AI generation. Latest Update (v0.5.9) - Reliable mlx-lm Detection : Settings and Dashboard now read the installed mlx-lm package metadata instead of importing its full runtime, preventing a valid installation from being shown as missing. - Setup Verification : Environment setup now verifies the installed mlx-lm version before reporting success. - uv Environment Setup Compatibility : The managed Python environment setup now rebuilds incomplete or existing .venv directories correctly with newer uv versions. - macOS Tahoe + MLX Training Stability : M-Courtya","default_branch":null,"files":null,"tree":[],"storefront":"/r/Mcourtyard","claimed":false,"request_supported":{"post":"https://gitbuyer.com/r/Mcourtyard/m-courtyard/request-supported","requests":0},"note":"indexed from public GitHub; nothing is for sale on this page. Clone it from GitHub. Paid listings live at /search."}