RNNLM + Dynamic KL Regularization

Training compute

5×10¹⁴ FLOP

Parameters

13.3M

Published

Jan 1, 2018

RNNLM + Dynamic KL Regularization is an AI model developed by Northwestern University (United States), first published in January 2018. It works in the language domain, on tasks such as language modeling.

Training it took an estimated 5×10¹⁴ FLOP of compute. The model has 13,275,200 parameters.

Access: Unreleased. Its weights are not openly released. The reference paper has 9 citations. Epoch AI rates the confidence of this record as likely.

Full record

Organization: Northwestern University
Country of organization: United States
Domain: Language
Task: Language modeling
Training compute: 5×10¹⁴ FLOP
Parameters: 13,275,200
Model accessibility: Unreleased
Open weights: No
Citations: 9
Epoch confidence: Likely