Learning Word Vectors for 157 Languages

Understand

Distributed word representations, or word vectors, have recently been applied to many tasks in natural language processing, leading to state-of-the-art performance.

• A key ingredient to the successful application of these representations is to train them on very large corpora, and use these pre-trained models in downstream tasks.
• In this paper, we describe how we trained such high quality word representations for 157 languages.
• We used two sources of data to train these models: the free online encyclopedia Wikipedia and data from the common crawl project.