embedding_matrix = np.zeros((len(word_index) + 1, 300))
for word, i in tqdm(word_index.items()):
embedding_vector = embeddings_index.get(word)
if embedding_vector is not None:
    embedding_matrix[i] = embedding_vector

ValueError                                Traceback (most recent call last)
<ipython-input-2-74b491f82363>
in <module>()
     48     embedding_vector = embeddings_index.get(word)
     49     if embedding_vector is not None:
---> 50         embedding_matrix[i] = embedding_vector
     51
     52 max_features = 200000

ValueError: could not broadcast input array from shape (25) into shape (300)