# How can I set vocab_size of BertModel(config=configuration).from_pretrained('bert-base-cased') to a higher value?

I have the following issue with the BERT transformer in python:

When I feed to BertModel().from_pretrained('bert-base-cased') an input obtained from BertTokenizer.from_pretrained('bert-base-cased') that contains a value bigger than 29000 I receive an error message saying that one of the indexes is out of range.

What I tried to do is to use BertConfig and set a vocab_size higher than 29000:

configuration = BertConfig(vocab_size=30_522)
bert = BertModel(config=configuration).from_pretrained('bert-base-cased')


Do you know where I can see which value of vocab_size is actually being used? Do you know how I can solve my issue?