Learning Word Vectors for 157 Languages

@article{Grave2018LearningWV,
  title={Learning Word Vectors for 157 Languages},
  author={Edouard Grave and Piotr Bojanowski and Prakhar Gupta and Armand Joulin and Tomas Mikolov},
  journal={CoRR},
  year={2018},
  volume={abs/1802.06893}
}
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… CONTINUE READING
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