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GPT-Neo: Large Scale Autoregressive Language Modeling with Mesh-Tensorflow

integration_instructionsResearch softwarekeyboard_double_arrow_right Software 21 Mar 2021Publisher:Zenodo
Authors: Black, Sid; Gao, Leo; Wang, Phil; Leahy, Connor; Biderman, Stella;

doi: 10.5281/zenodo.5297715 , 10.5281/zenodo.5297714 , 10.5281/zenodo.5551208

GPT-Neo: Large Scale Autoregressive Language Modeling with Mesh-Tensorflow

Abstract

GPT-Neo is an implementation of model & data-parallel GPT-2 and GPT-3-like models, utilizing Mesh Tensorflow for distributed support. This codebase is designed for TPUs. It should also work on GPUs, though we do not recommend this hardware configuration.

Keywords

Autoregressive language model, Transformers, Massive language model

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
views
OpenAIRE UsageCountsViews provided by UsageCounts
downloads
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57
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