 Tokenizer The training dataset was tokenized into subwords using a character level byte-pair encoding (``CharBPETokenizer``) with a vocabulary size of 50k tokens. The tokenizer itself was trained with a [tokenizers](https://github.com/huggingface/tokenizers) library.   We kindly encourage you to use the ``Fast`` version of the tokenizer, namely ``HerbertTokenizerFast``.  