Questions and Help
Description
Hi, we can use glove embedding when building vocab, using
something like:
MIN_FREQ = 2
TEXT.build_vocab(train_data,
min_freq = MIN_FREQ,
vectors = "glove.6B.300d",
unk_init = torch.Tensor.normal_)
However, I want to use BERT embedding because I need a sophisticated model to compare the performance of multiple embeddings. How can I use BERT in build_vocab?