gistfile1.txt

item_index = { str(i):i for i in range(931)}
embeddings_index={}
f = open( 'data/item_vectors.txt')
for line in f:
    values = line.split()
    word = values[0]
    coefs = np.asarray(values[1:], dtype='float32')
    embeddings_index[word] = coefs
f.close()


embedding_matrix = np.zeros((max_features, embed_size))
for word, i in item_index.items():
    if i < max_features:
        embedding_vector = embeddings_index.get(word)
        if embedding_vector is not None:
            embedding_matrix[i] = embedding_vector