M

mlx

MLX: An array framework for Apple silicon

🔧🔗https://github.com/transformerlab/transformerlab-api

API Server for Transformer Lab

🔧🔗https://github.com/transformerlab/transformerlab-app Open Source Application for Advanced LLM Engineering: interact, train, fine-tune, and evaluate large language models on your own computer

Examples in the MLX framework

🔧🔗https://github.com/transformerlab/galleries

Galleries for Models, Datasets, and Plugins used by Transformer Lab

Examples using MLX Swift

🔧🔗https://github.com/transformerlab/transformerlab-docs

Public Documentation for Transformer Lab

Swift API for MLX

🔧🔗https://github.com/Doriandarko/mlx-assistant

A simple script to enhance text editing across your Mac, leveraging the power of MLX. Designed for seamless integration, it offers real-time text correction everywhere you type.

🔧🔗https://github.com/Doriandarko/MLX-GRPO MLX-GRPO is a training framework for large language models (LLMs) that leverages Apple’s MLX framework exclusively. Designed to run natively on Apple Silicon using the Metal backend, this project implements Group-based Relative Policy Optimization (GRPO) with a chain-of-thought prompting structure. The pipeline includes dataset preparation, reward function definitions, and GRPO training—all running in a pure MLX environment (no CUDA).

Efficient framework-agnostic data loading

🔧🔗https://github.com/mainframecomputer/fullmoon-ios chat with private and local large language models

🔧🔗https://github.com/exo-explore/exo

Run your own AI cluster at home with everyday devices 📱💻 🖥️⌚

🔧🔗https://github.com/exo-explore/mlx-bitnet

1.58 Bit LLM on Apple Silicon using MLX

MLX support for the Open Neural Network Exchange (ONNX)

C API for MLX