The 'KeyedVectors' class in the 'gensim.models.keyedvectors' module of the Python library 'gensim' represents word embeddings and provides various methods for manipulating and querying them. It allows users to load pre-trained word vector files generated by popular algorithms like Word2Vec, GloVe, or FastText. The 'KeyedVectors' class enables efficient similarity search between words based on cosine similarity, retrieval of word vectors, and access to word counts and vocabulary information. It also allows for evaluating word similarities using word analogy tasks and performing algebraic operations on word vectors, such as vector addition and subtraction. This class serves as a powerful tool for natural language processing tasks, including semantic similarity, document classification, and machine translation.
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