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Stars
A set of beautifully-designed, accessible components and a code distribution platform. Works with your favorite frameworks. Open Source. Open Code.
Shared personal notes created while working with the Apple MLX machine learning framework
Train Large Language Models on MLX.
Fine-tune LLMs for free with guided Notebooks on Google Colab, Kaggle, and more.
MLX-Embeddings is the best package for running Vision and Language Embedding models locally on your Mac using MLX.
Graph Neural Network library made for Apple Silicon
A high-throughput and memory-efficient inference and serving engine for LLMs
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.
Run your own AI cluster at home with everyday devices 📱💻 🖥️⌚
Finetune Qwen3, Llama 4, TTS, DeepSeek-R1 & Gemma 3 LLMs 2x faster with 70% less memory! 🦥
An efficient C++17 GPU numerical computing library with Python-like syntax
Dataframes powered by a multithreaded, vectorized query engine, written in Rust
Explore a simple example of utilizing MLX for RAG application running locally on your Apple Silicon device.
Toolkit for linearizing PDFs for LLM datasets/training
"Deep Dive into AI with MLX and PyTorch" is an educational initiative designed to help anyone interested in AI, specifically in machine learning and deep learning, using Apple's MLX and Meta's PyTo…
Benchmark of Apple MLX operations on all Apple Silicon chips (GPU, CPU) + MPS and CUDA.
Phi-3.5 for Mac: Locally-run Vision and Language Models for Apple Silicon
MLX-VLM is a package for inference and fine-tuning of Vision Language Models (VLMs) on your Mac using MLX.
awni / mlx-examples
Forked from ml-explore/mlx-examplesExamples in the MLX framework