Arabic
Datasets
All datasets matching “Arabic”arabic-books
Arabic Books
Dataset Summary
The arabic-books dataset contains 8,500 rows of text, each representing the full text of a single Arabic book. These texts were extracted using the arabic-large-nougat model, showcasing the model’s capabilities in Arabic OCR and text extraction. The dataset spans a total of 1.1 billion tokens, calculated using the GPT-4 tokenizer.
This dataset is a testimony to the quality of the Arabic Nougat models and their effectiveness in extracting… See the full description on the dataset page: https://huggingface.co/datasets/MohamedRashad/arabic-books.traditionnals_arabic_shoes_splitArabicMMLU
Fajri Koto, Haonan Li, Sara Shatnawi, Jad Doughman, Abdelrahman Boda Sadallah, Aisha Alraeesi, Khalid Almubarak, Zaid Alyafeai, Neha Sengupta, Shady Shehata, Nizar Habash, Preslav Nakov, and Timothy Baldwin
MBZUAI, Prince Sattam bin Abdulaziz University, KFUPM, Core42, NYU Abu Dhabi, The University of Melbourne
Introduction
We present ArabicMMLU, the first multi-task language understanding benchmark for Arabic language, sourced from school exams across diverse… See the full description on the dataset page: https://huggingface.co/datasets/MBZUAI/ArabicMMLU.dialectal-arabic-lahgtna-v2
Dialectal Arabic Lahgtna v2
Large-scale multi-dialect Arabic speech dataset — 3,000+ hours across 13 Arabic dialects — for training and evaluating dialectal Arabic ASR systems. Part of the Lahgtna (لهجتنا) project for dialect-aware Arabic speech AI.
Dataset Summary
~611K utterances / 3,000+ hours of transcribed dialectal Arabic speech
**13 Arabic dialects **, labeled per utterance
16 kHz mono audio
Transcripts written in authentic dialectal orthography (not… See the full description on the dataset page: https://huggingface.co/datasets/oddadmix/dialectal-arabic-lahgtna-v2.arabic-stem-lexicon
Arabic Diacritized-Stem Lexicon
An undiacritized Arabic surface form → its most frequent diacritized stem.
Standard Arabic writes no short vowels, so anything that has to pronounce Arabic
must first put them back. A neural diacritizer does that well on rare words, where
inference is the only thing there is. On common words it is the wrong tool:
which vowels كتاب carries is not a thing to be inferred, it is a thing to be looked
up — and models get exactly these wrong, reading… See the full description on the dataset page: https://huggingface.co/datasets/TigreGotico/arabic-stem-lexicon.Arabic_Aya
Dataset Card for : Arabic Aya (2A)
Arabic Aya (2A) : A Curated Subset of the Aya Collection for Arabic Language Processing
Dataset Sources & Infos
Data Origin: Derived from 69 subsets of the original Aya datasets : CohereForAI/aya_collection, CohereForAI/aya_dataset, and CohereForAI/aya_evaluation_suite.
Languages: Modern Standard Arabic (MSA) and a variety of Arabic dialects ( 'arb', 'arz', 'ary', 'ars', 'knc', 'acm', 'apc', 'aeb', 'ajp', 'acq' )… See the full description on the dataset page: https://huggingface.co/datasets/2A2I/Arabic_Aya.