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What Are FP16/BF16 Precision Tricks?
In machine learning and neural network training, balancing speed and accuracy is a constant challenge. Using lower-precision formats like FP16 (16-bit floating point) and BF16 (bfloat16) can significantly accelerate computation and reduce memory usage. But these benefits come with challenges that require specific techniques and tricks to maintain model performance. This article explains what FP16 and BF16 are, their advantages, and practical tricks to effectively use these formats.
Written byAria Singh
Published onAugust 28, 2025
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