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MLX
MLX is a NumPy-like array framework designed for efficient and flexible machine learning on Apple silicon, brought to you by Apple machine learning research.
Open Source Application for Advanced LLM + Diffusion Engineering: interact, train, fine-tune, and evaluate large language models on your own computer.
A text-to-speech (TTS), speech-to-text (STT) and speech-to-speech (STS) library built on Apple's MLX framework, providing efficient speech analysis on Apple Silicon.
MLX-VLM is a package for inference and fine-tuning of Vision Language Models (VLMs) on your Mac using MLX.
A MLX port of FLUX based on the Huggingface Diffusers implementation.
This repository provides the code and model checkpoints for AIMv1 and AIMv2 research projects.
🤖✨ChatMLX is a modern, open-source, high-performance chat application for MacOS based on large language models.
Solve Puzzles. Learn Metal 🤘
Implementation of F5-TTS in MLX
MLX Omni Server is a local inference server powered by Apple's MLX framework, specifically designed for Apple Silicon (M-series) chips. It implements OpenAI-compatible API endpoints, enabling seamless integration with existing OpenAI SDK clients while leveraging the power of local ML inference.
Codam's own fixed, functioning and open source alternative of the miniLibX. MLX42 is a simple cross-platform graphics library running on GLFW and OpenGL.
Large Language Models (LLMs) applications and tools running on Apple Silicon in real-time with Apple MLX.
Generate accurate transcripts using Apple's MLX framework