preprocessing.py

from transformers import (
    AutoTokenizer,
)
from datasets import load_dataset


raw_datasets = load_dataset('lucadiliello/bookcorpusopen')
raw_datasets = raw_datasets['train'].train_test_split(test_size=0.05)

print(raw_datasets)

tokenizer = AutoTokenizer.from_pretrained('.')

seq_len = 512

def tokenize_fn(examples):
    return tokenizer(examples['text'],
                     max_length=seq_len,
                     return_overflowing_tokens=True,
                     truncation=True)

tokenized_datasets = raw_datasets.map(
    tokenize_fn,
    batched=True,
    batch_size=500,
    remove_columns=raw_datasets['train'].column_names,
)

tokenized_datasets.save_to_disk('data')