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View All on GitHub Clean up train diff tests 18 days ago
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mlcommons/algorithmic-efficiency mlcommons/algorithmic-efficiency MLCommons Algorithmic Efficiency is a benchmark and competition measuring neural network training speedups due to algorithmic improvements in both training algorithms and models.
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MLCommons Algorithmic Efficiency is a benchmark and competition measuring neural network training speedups due to algorithmic improvements in both training algorithms and models.
Python
Optimize Git Hook Configuration 9 months ago
Good First Issue
mlcommons/algorithmic-efficiency mlcommons/algorithmic-efficiency MLCommons Algorithmic Efficiency is a benchmark and competition measuring neural network training speedups due to algorithmic improvements in both training algorithms and models.
Open project →
425
MLCommons Algorithmic Efficiency is a benchmark and competition measuring neural network training speedups due to algorithmic improvements in both training algorithms and models.
Python