ERNIE-Doc (247M)

Training compute

3×10¹⁹ FLOP

Parameters

247M

Published

Dec 31, 2020

ERNIE-Doc (247M) is an AI model developed by Baidu (China), first published in December 2020. It works in the language domain, on tasks such as language modeling and language modeling/generation.

Training it took an estimated 3×10¹⁹ FLOP of compute (estimation method: operation counting). The model has 247,000,000 parameters. It was trained on roughly 103M datapoints.

Access: Open weights (unrestricted). Its weights are openly available. The reference paper has 64 citations. Epoch AI rates the confidence of this record as confident.

Full record

Organization: Baidu
Country of organization: China
Domain: Language
Task: Language modeling, Language modeling/generation
Training compute: 3×10¹⁹ FLOP
Compute estimation method: Operation counting
Parameters: 247,000,000
Dataset size: 103M
Model accessibility: Open weights (unrestricted)
Open weights: Yes
Citations: 64
Epoch confidence: Confident