tokenizer.py

from datasets import load_dataset
from transformers import AutoTokenizer

def get_training_corpus(dataset):
    """
    Returns the training corpus for the given dataset.
    """
    return (element['original_ja'] for element in iter(dataset))

dataset = load_dataset("snow_simplified_japanese_corpus", streaming=True, split="train")

train_dataset = dataset.skip(100)
val_dataset = dataset.take(100)

old_tokenizer = AutoTokenizer.from_pretrained("rinna/japanese-gpt2-small")
old_tokenizer = AutoTokenizer.from_pretrained("csebuetnlp/mT5_multilingual_XLSum")

print("Old Tokenizer:", old_tokenizer.tokenize("誰が一番に着くか私には分かりません。"))
new_tokenizer = old_tokenizer.train_new_from_iterator(get_training_corpus(train_dataset), 52000)

print("New Tokenizer:",new_tokenizer.tokenize("誰が一番に着くか私には分かりません。"))
new_tokenizer.save_pretrained("japanese-dummy-tokenizer")