Is there a way I can access just the vocabulary list of pre-trained vectors for word2vec and GloVe? I do not need the entire n-dimensional embeddings.
For the word2vec models, you probably can load them with the
gensim package and access the vocabulary using
from gensim.models.keyedvectors import KeyedVectors model = KeyedVectors.load_word2vec_format(filename, binary=True) words = model.wv.vocab
filename is the path to the pretrained model.
binary should be False if the pretrained model is in a text representation.