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ml-explore/mlx

mlx

MLX: An array framework for Apple silicon

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ml-explore

ml-explore

ml-explore • individual

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1,633

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Created

Nov 28, 2023

Project creation date

README Summary

MLX is an array framework designed specifically for machine learning on Apple silicon, offering NumPy-like APIs with automatic differentiation and lazy evaluation. It provides both Python and C++ APIs for building and training neural networks efficiently on Apple's M-series chips. The framework emphasizes ease of use while leveraging the unique capabilities of Apple silicon hardware.

AI Dev Skills

Unmapped

Array ComputingGPU ProgrammingApple Silicon OptimizationMachine Learning InfrastructureAutomatic DifferentiationNeural Network ImplementationMemory ManagementLazy Evaluation SystemsCross-platform ML Framework Development

Tags

Array ComputingGPU ProgrammingApple Silicon OptimizationMachine Learning InfrastructureAutomatic DifferentiationNeural Network ImplementationMemory ManagementLazy Evaluation SystemsCross-platform ML Framework DevelopmentML Model PrototypingScientific Computing on MacEdge ComputingOn-device AINumerical ArraysSelf-hostedNeural Network Inference OptimizationMachine Learning Model Training on Apple SiliconHardware-Optimized MLMathematical TensorsDeep Learning ResearchEdge/MobileC++

Taxonomy

Recent Activity

Updated 27 days ago

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Quality

beta
Quality
high
Maturity
beta

Categories

MLOps & InfrastructurePrimaryDev Tools & AutomationLearning ResourcesEvals & BenchmarkingML Platform & InfrastructureEdge & Mobile AISearch & KnowledgeOther AI / MLInference & ServingModel TrainingRobotics

PM Skills

Scale & ReliabilityDeveloper Platform

Languages

C++100.0%

Timeline

Project created
Nov 28, 2023
Forked
Mar 13, 2026
Your last push
27 days ago
Upstream last push
7 days ago
Tracked since
Mar 17, 2026

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