NCHLT Setswana GloVe embeddings

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dc.contact.email	Roald.Eiselen@nwu.ac.za
dc.contact.name	Roald Eiselen
dc.contributor.author	Roald Eiselen
dc.contributor.other	Rico Koen
dc.contributor.other	Albertus Kruger
dc.contributor.other	Jacques van Heerden
dc.date.accessioned	2023-07-28T08:11:12Z
dc.date.accessioned	2023-05-01
dc.date.available	2023-07-28T08:11:12Z
dc.date.available	2023-05-01
dc.date.issued	2023-05-01
dc.description	Static word embedding model based on the Global Vectors architecture (Pennington et al., 2014). The embeddings provide real-valued vector representations for Setswana text.
dc.format.extent	Training data: Paragraphs: 515,961; Token count: 14,518,437; Vocab size: 52,155; Embedding dimensions: 400;
dc.format.size	74.15MB (Zipped)
dc.identifier.uri	https://hdl.handle.net/20.500.12185/631
dc.language.iso	tn
dc.languages	Setswana
dc.media.category	Word embeddings
dc.media.type	Text
dc.project	NCHLT Text IV
dc.publisher	North-West University; Centre for Text Technology (CTexT)
dc.rights.license	Creative Commons Attribution 4.0 International (CC-BY 4.0)
dc.software.requirements	Python
dc.source	Web
dc.source	Government Documents
dc.title	NCHLT Setswana GloVe embeddings
dc.type	Modules

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