Neural Language Models for Nineteenth-Century English

We present four types of neural language models trained on a large historical dataset of books in English, published between 1760-1900 and comprised of ~5.1 billion tokens. The language model architectures include static (word2vec and fastText) and contextualized models (BERT and Flair). For each ar...

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Veröffentlicht in:	arXiv.org 2021-05
Hauptverfasser:	Hosseini, Kasra, Beelen, Kaspar, Colavizza, Giovanni, Mariona Coll Ardanuy
Format:	Artikel
Sprache:	eng
Schlagworte:	Datasets Static models
Online-Zugang:	Volltext
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