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Word embeddings trained with word2vec from the Suomi24 corpus 
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word2vec-menetelmällä harjoitetut sanaupotukset Suomi24-korpuksesta
suomi24-wordvec
Persistent Identifier of this resource:
http://urn.fi/urn:nbn:fi:lb-2022061701
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This package contains word embeddings trained with word2vec from Finnish Internet forum discussions from the Suomi24 corpus.
Instead of surface forms, the lemmas from text annotations were used. So inflected forms like "koiralta" are absent, and are instead all represented as the base form "koira".
The embedding file contains 633 758 entries. The dimension of the vector space is 128.
The embedding file is in a simple and easily parsed textual format produced by word2vec. The first line in the file gives the vocabulary size and dimension. Each line after that begins with a vocabulary item, followed by a space, followed by 128 floating point numbers (represented textually) each followed by a space. For efficient processing, look into converting this into a binary representation.
Instead of surface forms, the lemmas from text annotations were used. So inflected forms like "koiralta" are absent, and are instead all represented as the base form "koira".
The embedding file contains 633 758 entries. The dimension of the vector space is 128.
The embedding file is in a simple and easily parsed textual format produced by word2vec. The first line in the file gives the vocabulary size and dimension. Each line after that begins with a vocabulary item, followed by a space, followed by 128 floating point numbers (represented textually) each followed by a space. For efficient processing, look into converting this into a binary representation.
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