Is it possible to use Gensim for embeddings that are counted-based?

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Yes, Gensim can be used for counted-based embeddings, such as using the word co-occurrence matrix. The gensim.models module provides the CoOccurrences class, which can be used to create a word co-occurrence matrix from a corpus of documents. This matrix can then be used to train word embeddings using the Word2Vec class or other methods provided by the gensim.models module. However, compared to neural network-based embeddings like Word2Vec, counting-based embeddings are less common as they may not capture more complex relationships between words.