Modifying normalizer for pretrained tokenizers don't consistently work

🤗Tokenizers
1

I’m not sure if it’s a bug/feature but sometimes modifying the normalizer of a pretrained tokenizer works but sometimes it doesn’t.

For example, it works for "mistralai/Mistral-7B-v0.1" but not "mistralai/Mistral-7B-v0.3":

from transformers import AutoTokenizer
from tokenizers.normalizers import Sequence, Replace, Prepend

tokenizer_name = "mistralai/Mistral-7B-v0.1"
old_tok = AutoTokenizer.from_pretrained(tokenizer_name)

assert old_tok.backend_tokenizer.normalizer != None

new_normalizer = Sequence(
    [Prepend('▁'), Replace('▁', ' '), Replace("foo", "bar"), Replace('<br>', '\n')]
)

old_tok.backend_tokenizer.normalizer = new_normalizer
new_tokenizdr_name = f"new_tokenizer-{tokenizer_name}"
old_tok.save_pretrained(new_tokenizdr_name)


old_tok = AutoTokenizer.from_pretrained(tokenizer_name)
new_tok = AutoTokenizer.from_pretrained(new_tokenizdr_name)

[out]:

>>> print(' '.join(old_tok.batch_decode(old_tok("I foo you<br>hello world")['input_ids'])))
<s> I foo you < br > hello world

>>> print(' '.join(new_tok.batch_decode(new_tok("I foo you<br>hello world")['input_ids'])))
<s>  I  bar  you 
 hello  world

The same process above won’t work for "mistralai/Mistral-7B-v0.3".

2

Also raised issue on Modifying normalizer for pretrained tokenizers don't consistently work ¡ Issue #1552 ¡ huggingface/tokenizers ¡ GitHub

And asked on python - How do we add/modify the normalizer in a pretrained Huggingface tokenizer? - Stack Overflow

3

A few more follow-up questions:

  • How do we add/modify the normalizer in a pretrained Huggingface tokenizer?
  • Can any normalizer from a pretrained tokenizer be modified or just specific ones?
  • If the latter, why and how do we know if a pretrained tokenizer’s normalizer can be extended or modified?
  • Can we add a normalizer when the pretrained one doesn’t already have one?