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    MUSE

    MUSE

    A library for Multilingual Unsupervised or Supervised word Embeddings

    MUSE is a framework for learning multilingual word embeddings that live in a shared space, enabling bilingual lexicon induction, cross-lingual retrieval, and zero-shot transfer. It supports both supervised alignment with seed dictionaries and unsupervised alignment that starts without parallel data by using adversarial initialization followed by Procrustes refinement.
    Downloads: 2 This Week
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