hi sps.
I think it would be possible to use a Bert tokenizer with a Roberta Model, but you would have to train the Roberta model from scratch.   You wouldn’t be able to take advantage of transfer learning by using a pre-trained Roberta.
Why would you want to do that?
You might run into problems with things like the sep and cls tokens, which might have different conventions between Bert and Roberta, though I expect you could write some code to deal with that.
A tokenizer splits your text up into chunks, and replaces each chunk with a numerical value.   I think Bert and Roberta do this in different ways, but that shouldn’t make the systems incompatible.   Any embedding layer should be able to learn to use the numbers that come out of WordPiece, BytePair or SentencePiece tokenizers.
Have you seen this intro to tokenizers [Summary of the tokenizers — transformers 4.11.1 documentation 1]