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Meta's Multi-Token Prediction Makes LLMs Up to 3X Faster

May 6, 2024, 04:34 PM

Recent advancements in large language models (LLMs) have been highlighted by a new study from Meta researchers, which proposes a multi-token prediction approach to enhance the training and performance of these models. This method, which involves training LLMs to predict multiple future tokens simultaneously, has shown to significantly increase both the speed and efficiency of the models, potentially making them up to three times faster. The research, led by Gloeckle et al., has been recognized as a simple yet effective innovation that could improve the functionality of LLMs, particularly in coding, planning, and robotics applications.