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fineweb-edu-ar / README.md
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---
pretty_name: FWEAR
datasets:
- HuggingFaceTB/smollm-corpus
annotations_creators:
- no-annotation
language_creators:
- found
language:
- ar
- en
license:
- cc-by-nc-4.0
multilinguality:
- multilingual
size_categories:
- 100M<n<1B
source_datasets:
- HuggingFaceFW/fineweb-edu
task_categories:
- text-generation
- fill-mask
task_ids:
- language-modeling
- masked-language-modeling
dataset_info:
- config_name: en
features:
- name: text
dtype: string
splits:
- name: train
num_examples: 378810914
- config_name: ar
features:
- name: text
dtype: string
splits:
- name: train
num_examples: 378810914
configs:
- config_name: en
data_files:
- split: train
path: en/train/*.zip
- config_name: ar
data_files:
- split: train
path: ar/train/*.zip
extra_gated_fields:
Company: text
Country: country
I agree to use this dataset for non-commercial use ONLY: checkbox
---
# FineWeb-Edu-Ar
FineWeb-Edu-Ar is a machine-translated Arabic version of the FineWeb-Edu dataset designed to support the development of Arabic small language models (SLMs).
Dataset Details:
- Languages: Arabic, English (paired)
- Size: 202 billion tokens
- License: CC-BY-NC-4.0
- Source: Machine-translated from the deduplicated version of Hugging Face’s FineWeb-Edu dataset
- Translation model: facebook/nllb-200-distilled-600M
Application:
FineWeb-Edu-Ar is suitable for pre-training Arabic language models, especially those focused on general knowledge and common-sense reasoning. Researchers and developers can utilize this dataset to enhance the performance of Arabic SLMs across various NLP tasks.
Python Usage:
To load and utilize the FineWeb-Edu-Ar dataset in Python, you can use the datasets package:
```python
from datasets import load_dataset
dataset = load_dataset("kaust-generative-ai/fineweb-edu-ar", "ar", streaming=True)
print(next(iter(dataset["train"])))
```
Citation:
If you use FineWeb-Edu-Ar in your research, please cite the following paper:
https://arxiv.org/abs/2411.06402
```
@techreport{alrashed2024finewebeduar,
author = {Sultan Alrashed and Dmitrii Khizbullin and David R. Pugh},
title = {{FineWeb-Edu-Ar: Machine-translated Corpus to Support Arabic Small Language Models}},
institution = {{King Abdullah University of Science and Technology (KAUST)}},
year = {2024},
number = {arXiv:2411.06402},
url = {https://arxiv.org/abs/2411.06402}
}
```