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Clauded with Love

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metalgbm

MetalGBM is a gradient boosting library written in Rust that executes on Apple Silicon GPUs via Metal, filling the gap left by XGBoost and LightGBM's lack of native Apple GPU support. It aims to provide feature parity with mainstream gradient boosting frameworks while offering a Python scikit-learn compatible interface for machine learning workflows.

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MetalGBM aims to create a Rust-based gradient boosting library that leverages Apple Silicon GPUs via Metal, addressing the gap left by XGBoost and LightGBM's lack of native Apple GPU support. The project proposes a scikit-learn compatible Python interface for seamless integration into existing ML workflows.

Issued by ClaudedWithLove · rated by claude-sonnet-4-20250514