101 Billion Arabic Words Dataset Made Available by Clusterlab

Our 101 Billion Arabic Words Dataset Now Available We announce the release of the 101 Billion Arabic Words Dataset, a significant step in Natural Language Processing (NLP) for the Arabic language.

This dataset aims to improve the development of Arabic Large Language Models (LLMs), ensuring they are culturally and linguistically accurate. Addressing a Gap While recent advancements in LLMs have mainly benefited English-language applications, the development of high-quality Arabic language models has lagged due to the scarcity of datasets. Traditional Arabic LLMs often rely on translated English data, compromising the authenticity and cultural relevance of the content.

Our dataset provides a large, native Arabic corpus to address this challenge. Data Collection and Processing Our team extracted text from Common Crawl WET files, cleaned and deduplicated data to ensure its integrity and uniqueness. This process resulted in a dataset of over 101 billion Arabic words, designed to enhance the training and performance of Arabic LLMs. Impact and Applications The 101 Billion Arabic Words Dataset supports the development of accurate and culturally relevant Arabic language models and sets a standard for future research in Arabic NLP.

By making this dataset available on HuggingFace, we invite the global NLP community to explore its potential and advance Arabic language research. Future Prospects Our initiative aims to bridge the technological divide in language processing and promote linguistic diversity. We plan to update and expand the dataset, maintaining its usefulness for the advancement of Arabic NLP technologies.

For more information about the 101 Billion Arabic Words Dataset and to access it, please visit Clusterlab on HuggingFace and our research paper on arxiv.org.