def METHOD_NAME(self) -> None:
    # Build a vocab and get vectors twice to test caching.
    vectors = torchtext.vocab.GloVe(name="twitter.27B", dim="25")
    # The first 5 entries in each vector.
    expected_twitter = {
        "hello": [-0.77069, 0.12827, 0.33137, 0.0050893, -0.47605],
        "world": [0.10301, 0.095666, -0.14789, -0.22383, -0.14775],
    }
    for word in expected_twitter:
        self.assertEqual(vectors[word][:5], expected_twitter[word])
    self.assertEqual(vectors["<unk>"], torch.zeros(25))
    self.assertEqual(vectors["OOV token"], torch.zeros(25))