Wordvectors is a collection of pretrained word embeddings for more than 30 languages. It was created to make multilingual vector representations easier to obtain, especially for languages with fewer readily available resources than English. The repository provides models trained using both Word2Vec and fastText. Training corpora are constructed from Wikipedia database dumps using language-specific preprocessing when necessary. Scripts are included for corpus creation and for training new embeddings with either supported algorithm. Available languages include Chinese, Japanese, Korean, Spanish, French, German, Hindi, Russian, Vietnamese, Thai, and many others, with model metadata covering vector, corpus, and vocabulary sizes.
Features
- Pretrained multilingual word embeddings
- More than 30 supported languages
- Word2Vec model support
- fastText model support
- Wikipedia-based corpus generation
- Reusable vector training scripts