Question: use the 'bert - base - cased' from Huggingface as the underlying BERT model and the associated tokenizer. please compare the contextual embedding vectors of

use the 'bert-base-cased' from Huggingface as the underlying BERT model and the associated tokenizer.
please compare the contextual embedding vectors of 'bank' in the following four sentences:
"I need to bring my money to the bank today"
"I will need to bring my money to the bank tomorrow"
"I had to bank into a turn"
"The bank teller was very nice"
Inline Question #1:
Please calculate the pair-wise cosine similarities between 'bank' in the four sentences and fill in the table below. (Note, bank_i represent bank in the i_th sentence)
Please explain the results. Does it make sense?
use the 'bert - base - cased' from Huggingface as

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