Papers with W4A8 quantization

1 papers
Enhancing Computation Efficiency in Large Language Models through Weight and Activation Quantization (2023.emnlp-main)

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Challenge: Large language models (LLMs) are proficient in natural language processing tasks, but their deployment is limited by extensive parameter sizes and computational demands.
Approach: They propose a method to enhance computational efficiency in large language models by 4-bit weight and 8-bit activation quantization.
Outcome: The proposed techniques significantly boost task accuracies to levels comparable with full-precision models.

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