understanding word embeddings code example

Example: word embedding

from sklearn.linear_model import LogisticRegresion
from zeugma.embeddings import EmbeddingTransformer

glove = EmbeddingTransformer('glove')
x_train = glove.transform(corpus_train)

model = LogisticRegression()
model.fit(x_train, y_train)

x_test = glove.transform(corpus_test)
model.predict(x_test)