Should I need to use BERT embeddings while tokenizing using BERT tokenizer? I am new to BERT and NLP and I am a little confused with tokenization and word embedding.
My doubt is if I use the BertTokenizer for tokenizing a sentence then do I have to compulsorily use BertEmbedding for generating its corresponding word vectors of the tokens or I can train my own word2vec model to generate my word embedding while using BertTokenizer?
Pardon me if this question doesn't make any sense.
word2vec and BERT are completely different things. You don't need to use BERT Tokenizer for training word2vec model. But, if you want to go ahead. Here's a link which can help you.