NAS with base 8 and shared embeddings

Training compute

1.1×10¹⁶ FLOP

Parameters

54M

Published

Nov 5, 2016

NAS with base 8 and shared embeddings is an AI model developed by Google Brain (United States), first published in November 2016. It works in the language domain, on tasks such as language modeling and neural architecture search - nas.

Training it took an estimated 1.1×10¹⁶ FLOP of compute (estimation method: operation counting). The model has 54,000,000 parameters. It was trained on roughly 929K datapoints.

Access: Unreleased. Its weights are not openly released. The reference paper has 5,894 citations. Epoch AI rates the confidence of this record as confident.

Full record

Organization: Google Brain
Country of organization: United States
Domain: Language
Task: Language modeling, Neural Architecture Search - NAS
Training compute: 1.1×10¹⁶ FLOP
Compute estimation method: Operation counting
Parameters: 54,000,000
Dataset size: 929K
Model accessibility: Unreleased
Open weights: No
Citations: 5,894
Epoch confidence: Confident