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E-Sparse: Boosting the Large Language Model Inference through Entropy-based N:M Sparsity
Traditional pruning methods are known to be challenging to work in Large Language Models (LLMs) for Generative AI because of their unaffordable training process and large computational demands.
MKQ-BERT: Quantized BERT with 4-bits Weights and Activations
In this work, we propose MKQ-BERT, which further improves the compression level and uses 4-bits for quantization.
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