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docs
.
Pretrained BERT base language model for Arabic
If you use this model in your work, please cite this paper:
@misc{safaya2020kuisail,
title={KUISAIL at SemEval-2020 Task 12: BERT-CNN for Offensive Speech Identification in Social Media},
author={Ali Safaya and Moutasem Abdullatif and Deniz Yuret},
year={2020},
eprint={2007.13184},
archivePrefix={arXiv},
primaryClass={cs.CL}
}
arabic-bert-base
model was pretrained on ~8.2 Billion words:
and other Arabic resources which sum up to ~95GB of text.
Notes on training data:
You can use this model by installing torch
or tensorflow
and Huggingface library transformers
. And you can use it directly by initializing it like this:
from transformers import AutoTokenizer, AutoModel
tokenizer = AutoTokenizer.from_pretrained("asafaya/bert-base-arabic")
model = AutoModel.from_pretrained("asafaya/bert-base-arabic")
For further details on the models performance or any other queries, please refer to Arabic-BERT
Thanks to Google for providing free TPU for the training process and for Huggingface for hosting this model on their servers π