region:us
TODO: Probably we need to add the spaces to the end of the vocab!!! Despite being useless!!!

This is https://huggingface.co/NeelNanda/gpt-neox-tokenizer-digits but with a fix that makes this work on `tokenizers == 0.14` after a breaking change involving `added_tokens`: https://github.com/huggingface/tokenizers/issues/1358

The two changes from NeelNanda/gpt-neox-tokenizer-digits are 
1) (Important) we remove the space tokens from the "added_tokens" key in `tokenizer.json` here: https://huggingface.co/ArthurConmy/alternative-neel-tokenizer/blob/main/tokenizer.json . These caused the breaking change along with the tokenizers PR above
2) (Not important) we use `GPTNeoXTokenizer` rather than `PretrainedTokenizerFast` in `tokenizer_config.json` as this seemed to match what GPT-NeoX did

# Neel's README

This is a fork of the GPT NeoX 20B tokenizer, edited to split every numerical digit into a separate token. This has the goal of making it easier for the model to learn arithmetic capabilities and to hopefully be more interpretable, and copies the idea from the [PaLM tokenizer](https://ai.googleblog.com/2022/04/pathways-language-model-palm-scaling-to.html). 

This was done, extremely hackily, by just removing every token that contained "\d\d" (eg "2013"). All remaining digit containing tokens are "0" ... "9" and " 0" ... " 9"

This comes at the cost of making modelling normal text harder, since eg dates like 2013 which naturally *should* be a single token are now 2|0|1|3.

This has a reduced vocab size of 48252 (several of the tokens towards the end are special whitespace tokens copied in from GPT-NeoX to make tokenizing code easier - some of these are duplicated in the vocabulary and thus may not actually show up at train time).

It includes a padding token (<|PAD|>) an End-Of-String token (<|EOS|>) and a Beginning-Of-String token (<|BOS|>)