Word2Vec (small)

Parameters

207.6M

Published

Oct 16, 2013

Word2Vec (small) is an AI model developed by Google (United States), first published in October 2013. It works in the language domain, on tasks such as semantic embedding.

Epoch AI has no training-compute estimate for this model. The model has 207,600,000 parameters. It was trained on roughly 10B datapoints.

The reference paper has 35,201 citations.

Full record

Organization: Google
Country of organization: United States
Domain: Language
Task: Semantic embedding
Parameters: 207,600,000
Dataset size: 10B
Citations: 35,201