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---
license: cc-by-sa-4.0
language:
- ja
dataset_info:
features:
- name: text
dtype: string
splits:
- name: train
num_bytes: 1954209746
num_examples: 745392
- name: validation
num_bytes: 107186201
num_examples: 41576
- name: test
num_bytes: 107509760
num_examples: 41268
download_size: 420085060
dataset_size: 2168905707
---
This dataset is a reformatted version of the Japanese portion of [wiki40b](https://aclanthology.org/2020.lrec-1.297/) dataset.
When you use this dataset, please cite the original paper:
```
@inproceedings{guo-etal-2020-wiki,
title = "{W}iki-40{B}: Multilingual Language Model Dataset",
author = "Guo, Mandy and
Dai, Zihang and
Vrande{\v{c}}i{\'c}, Denny and
Al-Rfou, Rami",
booktitle = "Proceedings of the Twelfth Language Resources and Evaluation Conference",
month = may,
year = "2020",
address = "Marseille, France",
publisher = "European Language Resources Association",
url = "https://aclanthology.org/2020.lrec-1.297",
pages = "2440--2452",
abstract = "We propose a new multilingual language model benchmark that is composed of 40+ languages spanning several scripts and linguistic families. With around 40 billion characters, we hope this new resource will accelerate the research of multilingual modeling. We train monolingual causal language models using a state-of-the-art model (Transformer-XL) establishing baselines for many languages. We also introduce the task of multilingual causal language modeling where we train our model on the combined text of 40+ languages from Wikipedia with different vocabulary sizes and evaluate on the languages individually. We released the cleaned-up text of 40+ Wikipedia language editions, the corresponding trained monolingual language models, and several multilingual language models with different fixed vocabulary sizes.",
language = "English",
ISBN = "979-10-95546-34-4",
}
```
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