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/20.500.12185/663Static word embeddings for the Skipgram flavour of the word2vec (w2v) architecture (Mikolov et al., 2013). The embedding provides real-valued vector representations for Tshivenḓa text.Training data: Paragraphs: 304,248; Token count: 7,363,713; Vocab size: 52,778; Embedding dimensions: 400;veModules75.55MB (Zipped)