AraVec is an open-source Arabic word embedding project that offers distributed word representations (vectors) trained on over 1.1 billion Arabic tokens from tweets and Wikipedia articles. It provides both unigram and n-gram models built using the gensim library’s Word2Vec implementation. These pre-trained embeddings can be loaded and used for various Arabic NLP tasks such as text classification, sentiment analysis, and information retrieval.