Hi,
I am new to using transformer based models. I have a few basic questions, hopefully, someone can shed light, please.
I’ve been training GloVe and word2vec on my corpus to generate word embedding, where a unique word has a vector to use in the downstream process. Now, my questions are:

Can we generate a similar embedding using the BERT model on the same corpus?
Can we have one unique word with its vector? BERT is contextual, not sure how the vector will look like for the same word which is repeated in different sentences.
If a word is repeated and not unique, not sure how I can use these vectors in the downstream process.

Appreciate your valuable inputs. I tried to look over the internet but was not able to find a clear answer. If someone can help with the above it will be really helpful.
Thanks