Arabertmo Base V3

🚀 Arabic BERT Model

AraBERTMo is an Arabic pre - trained language model based on Google's BERT architecture. It provides a powerful solution for Arabic language processing tasks, leveraging the well - known BERT framework.

Tags

• Fill - Mask

Datasets

• OSCAR

Widget Examples

• " السلام عليكم ورحمة[MASK] وبركاتة"
• " اهلا وسهلا بكم في [MASK] من سيربح المليون"
• " مرحبا بك عزيزي الزائر [MASK] موقعنا "

🚀 Quick Start

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("Ebtihal/AraBertMo_base_V3")
model = AutoModelForMaskedLM.from_pretrained("Ebtihal/AraBertMo_base_V3")

✨ Features

• AraBERTMo_base uses the same BERT - Base config.
• AraBERTMo_base now comes in 10 new variants.
• All models are available on the HuggingFace model page under the Ebtihal name.
• Checkpoints are available in PyTorch formats.

📦 Installation

To use this model, you need to install the following libraries:

• torch or tensorflow
• Huggingface library transformers

📚 Documentation

Pretraining Corpus

The AraBertMo_base_V3 model was pre - trained on ~3 million words from the following source:

• OSCAR - Arabic version "unshuffled_deduplicated_ar".

Training Results

This model achieves the following results:

Research Background

This model was built for master's degree research in the following organization:

• University of kufa.
• Faculty of Computer Science and Mathematics.
• Department of Computer Science