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NCHLT Sepedi FLAIR-forward embeddings
Contextual word/string embeddings for the forward flavour of the FLAIR architecture (Akbik et al., 2018). The embedding provides real-valued vector representations for Sepedi text.
Roald Eiselen
Roald.Eiselen@nwu.ac.za
North-West University; Centre for Text Technology (CTexT)
Creative Commons Attribution 4.0 International (CC-BY 4.0)
Sepedi
Roald Eiselen
Rico Koen; Albertus Kruger; Jacques van Heerden
https://hdl.handle.net/20.500.12185/618
Text
Modules
String embeddings
Training data: Paragraphs: 292,594; Token count: 8,908,709; Vocab size: N/A; Embedding dimensions: 2,048;
182.21MB (Zipped)
NCHLT Text IV
Python
Web; Government Documents
nso
2023-07-28T08:10:34Z; 2023-05-01
2023-07-28T08:10:34Z; 2023-05-01
2023-05-01


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  • Resource Catalogue [349]
    A collection of language resources available for download from the RMA of SADiLaR. The collection mostly consists of resources developed with funding from the Department of Arts and Culture.

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