MLX
Frameworks
MLX

Provide machine learning exploration tools, support model training and data analysis.

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【Application Scenarios】

  • Work scenario: Machine learning research and development
  • Life scenario: Not applicable

【Target Users】

  • Machine learning researchers
  • Developers

【Core Features】

  • NumPy-like array framework
  • Automatic differentiation
  • Automatic vectorization
  • Computational graph optimization
  • Multi-device support (CPU, GPU)

【Is It Free】

  • Yes

【Community Ecosystem】

  • Supported by the Apple machine learning research team
  • Has Python and C++ API

【Summary】

  • MLX is a NumPy-like array framework designed for Apple silicon, supporting efficient machine learning research and development, with core features such as automatic differentiation, automatic vectorization, computational graph optimization, etc., supports multi-device operations, and is completely free.
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