Datasets:

Modalities:
Text
Formats:
parquet
Languages:
Chinese
ArXiv:
Libraries:
Datasets
Dask
License:
fineweb-zhtw / README.md
voidful's picture
Update README.md
588aa4d verified
metadata
dataset_info:
  features:
    - name: text
      dtype: string
    - name: id
      dtype: string
    - name: metadata
      struct:
        - name: dump
          dtype: string
        - name: url
          dtype: string
        - name: date
          dtype: timestamp[s]
        - name: file_path
          dtype: string
        - name: language
          dtype: string
        - name: language_score
          dtype: float64
        - name: language_script
          dtype: string
        - name: minhash_cluster_size
          dtype: int64
        - name: top_langs
          dtype: string
        - name: avg_words_per_line
          dtype: float64
  splits:
    - name: train
      num_bytes: 160689800579
      num_examples: 48058113
  download_size: 107457281288
  dataset_size: 160689800579
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/train-*
license: odc-by
language:
  - zh
pretty_name: z

Fineweb-zhtw

Overview / 概覽

This repository contains the Fineweb-zhtw dataset, a large-scale collection of Traditional Chinese text data mined from the web. It is built upon the HuggingFaceFW/fineweb-2 dataset with modifications provided by mtkresearch/fineweb-zhtw.

本專案提供 Fineweb-zhtw 資料集,為大規模的繁體中文網路文本資料。此資料集基於 HuggingFaceFW/fineweb-2 並經由 mtkresearch/fineweb-zhtw 進行修改。

https://github.com/voidful/fineweb-zhtw/tree/main

Dataset Details / 資料集細節

  • Data Size: 107 GB of text data

  • Number of Entries: 48,058,113

  • Estimated Tokens: 72B

  • 資料量: 107 GB 純文字資料

  • 資料筆數: 48,058,113 筆

  • 預估 Token 數: 72B

Citation / 引用

For academic citations, please use the following BibTeX entry:

@misc{lin2024finewebzhtwscalablecurationtraditional,
      title={FineWeb-zhtw: Scalable Curation of Traditional Chinese Text Data from the Web}, 
      author={Cheng-Wei Lin and Wan-Hsuan Hsieh and Kai-Xin Guan and Chan-Jan Hsu and Chia-Chen Kuo and Chuan-Lin Lai and Chung-Wei Chung and Ming-Jen Wang and Da-Shan Shiu},
      year={2024},
      eprint={2411.16387},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={https://arxiv.org/abs/2411.16387}, 
}

Additional Information / 附加資訊

For further questions or details, please refer to the repository or contact the maintainers. me@eric-lam.com

如有任何疑問或需進一步資訊,請參考本專案或聯絡維護者。me@eric-lam.com