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Which of the following Python code snippets correctly demonstrates how to load pre-trained word embeddings (e.g., GloVe or Word2Vec) using spaCy and then calculate the cosine similarity between two words?
Correct Answer: B,C,D,E
Option A loads a small spacy model without word vectors. Option B loads the large spacy model with word vectors correctly, and calculates the similarity. Option C correctly loads word embeddings from a text file and uses cosine_similarity from sklearn.metrics.pairwise to get similarity Option D shows word similarity and usage of the gensim model.