Load Pretrained glove vectors in python

glove model files are in a word - vector format. You can open the textfile to verify this. Here is a small snippet of code you can use to load a pretrained glove file:

import numpy as np

def load_glove_model(File):
    print("Loading Glove Model")
    glove_model = {}
    with open(File,'r') as f:
        for line in f:
            split_line = line.split()
            word = split_line[0]
            embedding = np.array(split_line[1:], dtype=np.float64)
            glove_model[word] = embedding
    print(f"{len(glove_model)} words loaded!")
    return glove_model

You can then access the word vectors by simply using the gloveModel variable.

print(gloveModel['hello'])

You can do it much faster with pandas:

import pandas as pd
import csv

words = pd.read_table(glove_data_file, sep=" ", index_col=0, header=None, quoting=csv.QUOTE_NONE)

Then to get the vector for a word:

def vec(w):
  return words.loc[w].as_matrix()

And to find the closest word to a vector:

words_matrix = words.as_matrix()

def find_closest_word(v):
  diff = words_matrix - v
  delta = np.sum(diff * diff, axis=1)
  i = np.argmin(delta)
  return words.iloc[i].name