Mogrifier RLSTM (WT2)

Training compute

1.4×10¹⁷ FLOP

Parameters

35M

Published

Nov 3, 2022

Mogrifier RLSTM (WT2) is an AI model developed by DeepMind (United Kingdom), first published in November 2022. It works in the language domain, on tasks such as language modeling.

Training it took an estimated 1.4×10¹⁷ FLOP of compute (estimation method: operation counting). The model has 35,000,000 parameters. It was trained on roughly 2.7M datapoints.

Access: Unreleased. Its weights are not openly released. Epoch AI rates the confidence of this record as confident.

Full record

Organization: DeepMind
Country of organization: United Kingdom
Domain: Language
Task: Language modeling
Training compute: 1.4×10¹⁷ FLOP
Compute estimation method: Operation counting
Parameters: 35,000,000
Dataset size: 2.7M
Model accessibility: Unreleased
Open weights: No
Citations: 0
Epoch confidence: Confident