metadata

dataset_info:
  features:
    - name: text
      dtype: string
  splits:
    - name: train
      num_bytes: 4023336586
      num_examples: 23700035
    - name: test
      num_bytes: 25881716
      num_examples: 150820
  download_size: 2027128319
  dataset_size: 4049218302
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/train-*
      - split: test
        path: data/test-*
license: odc-by
language:
  - ar
tags:
  - Egyptian
  - Arabic
  - dataset
  - fineweb2
pretty_name: Egyptian Arabic
size_categories:
  - 10M<n<100M

FineWeb2 Egyptian Arabic

🇪🇬 This is the Egyptian Arabic Portion of The FineWeb2 Dataset.

🇪🇬 This dataset contains a rich collection of text in Egyptian Arabic (ISO 639-3: arz), a widely spoken dialect within the Afro-Asiatic language family.

🇪🇬 With over 439 million words and 1.4 million documents, it serves as a valuable resource for NLP development and linguistic research focused on Egyptian Arabic.

Purpose of This Repository

This repository provides easy access to the Arabic portion - Egyptian of the extensive FineWeb2 dataset. My primary goal is to make this valuable data more accessible and impactful for researchers, developers, and anyone working on Arabic natural language processing (NLP) projects.

By focusing on Arabic, I aim to:

Simplify Access: Provide a direct and streamlined way to download the Arabic portion of the dataset without navigating through the larger collection.
Promote Research: Enable more efficient use of Arabic text data for NLP, LLMs, and linguistic research.
Empower the Community: Support Arabic language processing and contribute to the growth of multilingual NLP capabilities.
Encourage Collaboration: Foster an environment where researchers and developers can build impactful applications using Arabic data.

Credit to the Original Work

The dataset is released under the Open Data Commons Attribution License (ODC-By) v1.0, with additional usage subject to CommonCrawl's Terms of Use..

Citation

If you use this dataset, please cite it as follows:

@software{penedo2024fineweb-2,
  author = {Penedo, Guilherme and Kydlíček, Hynek and Sabolčec, Vinko and Messmer, Bettina and Foroutan, Negar and Jaggi, Martin and von Werra, Leandro and Wolf, Thomas},
  title = {FineWeb2: A sparkling update with 1000s of languages},
  month = dec,
  year = 2024,
  doi = {10.57967/hf/3744},
  url = {https://huggingface.co/datasets/HuggingFaceFW/fineweb-2}
}