View source for Embeddings

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For Large Language Models, we refer to [[Language_Modeling]].

== Word2Vec embeddings== <!--T:2-->

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Repository for the word embeddings described in Evaluating Unsupervised Dutch Word Embeddings as a Linguistic Resource, presented at LREC 2016.
* [https://github.com/clips/dutchembeddings Download page]

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== FastText embeddings==
Word vectors in 157 languages trained on CommonCrawl and Wikipedia corpora.
* [https://fasttext.cc/docs/en/crawl-vectors.html Download page]

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==Coosto embeddings==
This repository contains a Word2Vec model trained on a large Dutch corpus, comprised of social media messages and posts from Dutch news, blog and fora. 

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* [https://github.com/coosto/dutch-word-embeddings Github page]

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==GeenStijl.nl embeddings ==
GeenStijl.nl embeddings contains over 8M messages from the controversial Dutch websites GeenStijl and Dumpert to train a word embedding model that captures the toxic language representations contained in the dataset. The trained word embeddings (±150MB) are released for free and may be useful for further study on toxic online discourse.

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*[https://www.textgain.com/portfolio/geenstijl-embeddings/ Project page]
*[https://www.textgain.com/wp-content/uploads/2021/06/TGTR4-geenstijl.pdf Report]
*[https://www.textgain.com/projects/geenstijl/geenstijl_embeddings.zip Download page]

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==NLPL Word Embeddings Repository==
Made by the University of Oslo. Models trained with clearly stated hyperparameters, on clearly described and linguistically pre-processed corpora.

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For Dutch, Word2Vec and ELMO embeddings are available.

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*[http://vectors.nlpl.eu/repository/ Repository page]
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