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/20.500.12185/665Static word embeddings for the Skipgram flavour of the word2vec (w2v) architecture (Mikolov et al., 2013). The embedding provides real-valued vector representations for isiZulu text.Training data: Paragraphs: 816,776; Token count: 15,801,081; Vocab size: 101,924; Embedding dimensions: 600;zuModules218.64MB (Zipped)