A library for Multilingual Unsupervised or Supervised word Embeddings
MUSE: Multilingual Unsupervised and Supervised Embeddings
A library for Multilingual Unsupervised or Supervised word Embeddings.
MUSE is a Python library for multilingual word embeddings, whose goal is to provide the community with:
- state-of-the-art multilingual word embeddings (fastText embeddings aligned in a common space)
- large-scale high-quality bilingual dictionaries for training and evaluation
We include two methods, one supervised that uses a bilingual dictionary or identical character strings, and one unsupervised that does not use any parallel data (see Word Translation without Parallel Data for more details).
Dependencies
MUSE is available on CPU or GPU, in Python 2 or 3. Faiss is optional for GPU users – though Faiss-GPU will greatly speed up nearest neighbor search – and highly recommended for CPU users. Faiss can be installed using