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--- |
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dataset_info: |
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features: |
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- name: content |
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dtype: string |
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splits: |
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- name: train |
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num_bytes: 17882150544 |
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num_examples: 12328228 |
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download_size: 12940914691 |
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dataset_size: 17882150544 |
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--- |
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# CC-100 zh-Hant (Traditional Chinese) |
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From https://data.statmt.org/cc-100/, only zh-Hant - Chinese (Traditional). Broken into paragraphs, with each paragraphs as a row. |
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Estimated to have around 4B tokens when tokenized with the [`bigscience/bloom`](https://huggingface.co/bigscience/bloom) tokenizer. |
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There's another version that the text is split by lines instead of paragraphs: [`zetavg/CC-100-zh-Hant`](https://huggingface.co/datasets/zetavg/CC-100-zh-Hant). |
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## References |
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Please cite the following if you found the resources in the CC-100 corpus useful. |
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* **Unsupervised Cross-lingual Representation Learning at Scale**, *Alexis Conneau, Kartikay Khandelwal, Naman Goyal, Vishrav Chaudhary, Guillaume Wenzek, Francisco Guzmán, Edouard Grave, Myle Ott, Luke Zettlemoyer, Veselin Stoyanov*, Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics (ACL), p. 8440-8451, July 2020, [pdf](https://www.aclweb.org/anthology/2020.acl-main.747.pdf), [bib](https://www.aclweb.org/anthology/2020.acl-main.747.bib) . |
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* **CCNet: Extracting High Quality Monolingual Datasets from Web Crawl Data**, *Guillaume Wenzek, Marie-Anne Lachaux, Alexis Conneau, Vishrav Chaudhary, Francisco Guzmán, Armand Joulin, Edouard Grave*, Proceedings of the 12th Language Resources and Evaluation Conference (LREC), p. 4003-4012, May 2020, [pdf](https://www.aclweb.org/anthology/2020.lrec-1.494.pdf), [bib](https://www.aclweb.org/anthology/2020.lrec-1.494.bib). |
