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Scaling Language Models: Methods, Analysis Insights from Training Gopher
[article]
2022
arXiv
pre-print
Language modelling provides a step towards intelligent communication systems by harnessing large repositories of written human knowledge to better predict and understand the world. In this paper, we present an analysis of Transformer-based language model performance across a wide range of model scales -- from models with tens of millions of parameters up to a 280 billion parameter model called Gopher. These models are evaluated on 152 diverse tasks, achieving state-of-the-art performance across
arXiv:2112.11446v2
fatcat:wtajhbesibbetikkpow2vwiwqq