ReLU Strikes Back: Exploiting Activation Sparsity in Large Language Models

ReLU Strikes Back: Exploiting Activation Sparsity in Large Language Models

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Reinstating ReLU Activation in Large Language Models

Large Language Models (LLMs) with billions of parameters have transformed AI applications, but their demanding computation during inference poses challenges for deployment on resource-constrained devices. Our study strongly advocates for using ReLU activation in LLMs, which has a negligible impact on convergence and performance while significantly reducing computation and weight transfer.

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