Accelerating Large Language Models with Mixed-Precision Techniques
Read OriginalThis technical article explains how mixed-precision training using lower-precision formats like 16-bit and 32-bit floats can accelerate large language models (LLMs). It details the memory and computational benefits, achieving up to 3x speedups in training and inference on modern GPUs while maintaining model accuracy, with examples relevant to PyTorch and deep learning.
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