Exploratory data analysis (EDA) is a powerful technique to understand the structure of word embeddings, the basis of large language models. In this article, we'll apply EDA to GloVe word embeddings and find some interesting insights.
from gensim.scripts.glove2word2vec import glove2word2vec
glove2word2vec(glove_input_file=file, word2vec_output_file="gensim_glove_vectors.txt")
from gensim.models.keyedvectors import KeyedVectors
model = KeyedVectors.load_word2vec_format("gensim_glove_vectors.txt", binary=False)
glove2word2vec(glove_input_file=file, word2vec_output_file="gensim_glove_vectors.txt")
from gensim.models.keyedvectors import KeyedVectors
model = KeyedVectors.load_word2vec_format("gensim_glove_vectors.txt", binary=False)
