Information
A word2vec model trained by Kjetil Bugge Kristoffersen (kjetilbk@ifi.uio.no) on a vocabulary of size 2000000 corresponding to 135159000000 tokens from the dataset ENC3:_English_Common_Crawl_Corpus.
The model is trained with the following properties: no lemmatization and postag with the algorith Global Vectors with window of 10 and dimension of 300.
How to use?
from gensim.models import KeyedVectors
from huggingface_hub import hf_hub_download
model = KeyedVectors.load_word2vec_format(hf_hub_download(repo_id="Word2vec/nlpl_82", filename="model.bin"), binary=True, unicode_errors="ignore")
Citation
Fares, Murhaf; Kutuzov, Andrei; Oepen, Stephan & Velldal, Erik (2017). Word vectors, reuse, and replicability: Towards a community repository of large-text resources, In Jörg Tiedemann (ed.), Proceedings of the 21st Nordic Conference on Computational Linguistics, NoDaLiDa, 22-24 May 2017. Linköping University Electronic Press. ISBN 978-91-7685-601-7
This archive is part of the NLPL Word Vectors Repository (http://vectors.nlpl.eu/repository/), version 2.0, published on Friday, December 27, 2019. Please see the file 'meta.json' in this archive and the overall repository metadata file http://vectors.nlpl.eu/repository/20.json for additional information. The life-time identifier for this model is: http://vectors.nlpl.eu/repository/20/82.zip
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