Uzbek 65 million web corpus Word2Vec model

Word2Vec model developed from 65 million Uzbek web corpus (10.5281/zenodo.19462612). The model can be used for efficient text representation via Word embeddings (vector representations). A simple Python script for loading and using the model. Word2vec is a group of related models that are used to produce word embeddings. These models are shallow, two-layer neural networks that are trained to reconstruct linguistic contexts of words. The Word2Vec implementation used to produce the model, which can later be used for the model, was Gensim.

Hali tarjima qilinmagan