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/20.500.12185/630Static word embedding model based on the Global Vectors architecture (Pennington et al., 2014). The embeddings provide real-valued vector representations for Sesotho text.Training data: Paragraphs: 535,853; Token count: 17,425,650; Vocab size: 53,051; Embedding dimensions: 400;stModules75.60MB (Zipped)