Creative Commons Attribution 4.0 International (CC-BY 4.0)Roald EiselenRico KoenAlbertus KrugerJacques van Heerden2023-07-282023-05-012023-07-282023-05-012023-05-01https://hdl.handle.net/20.500.12185/635Static word embedding model based on the Global Vectors architecture (Pennington et al., 2014). The embeddings provide real-valued vector representations for isiZulu text.Training data: Paragraphs: 816,776; Token count: 15,801,081; Vocab size: 477,993; Embedding dimensions: 300;zuModules503.56MB (Zipped)