Learning to Route by Task for Efficient Inference

Posted by Sneha Kudugunta, Research Software Engineer and Orhan Firat, Research Scientist, Google Research

Scaling large language models has resulted in significant quality improvements natural language understanding (T5), generation (GPT-3) and multilingual neural machine translation (M4). One common approach to building a larger model is to increase the depth (number of layers) and width (layer dimensionality), simply enlarging existing dimensions of the network. Such dense models take an input sequence (divided into smaller components, …

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