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README.md
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---
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language: rus
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license: cc-by-4.0
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tags:
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- word2vec
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datasets: Russian_National_Corpus
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---
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## Information
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A word2vec model trained by Andrey Kutuzov (andreku@ifi.uio.no) on a vocabulary of size 249333 corresponding to 270000000 tokens from the dataset `Russian_National_Corpus`.
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The model is trained with the following properties: lemmatization and postag with the algorith Gensim Continuous Bag-of-Words with window of 10 and dimension of 300.
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## How to use?
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```
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from gensim.models import KeyedVectors
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from huggingface_hub import hf_hub_download
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model = KeyedVectors.load_word2vec_format(hf_hub_download(repo_id="Word2vec/nlpl_220", filename="model.bin"), binary=True, unicode_errors="ignore")
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```
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## Citation
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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
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This archive is part of the NLPL Word Vectors Repository (http://vectors.nlpl.eu/repository/), version 2.0, published on Friday, December 27, 2019.
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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.
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The life-time identifier for this model is: http://vectors.nlpl.eu/repository/20/220.zip
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