Arabertmo Base V2

🚀 Arabic BERT Model

AraBERTMo is an Arabic pre - trained language model based on Google's BERT architecture, offering multiple variants and achieving good results in tasks like Fill - Mask.

🚀 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_V2")
model = AutoModelForMaskedLM.from_pretrained("Ebtihal/AraBertMo_base_V2")

✨ Features

• Multiple Variants: AraBERTMo_base now comes in 10 new variants.
• Available on HuggingFace: All models are available on the HuggingFace model page under the Ebtihal name.
• PyTorch Format: Checkpoints are available in PyTorch formats.

📦 Installation

To use this model, you need to install torch or tensorflow and the Huggingface library transformers.

📚 Documentation

Pretraining Corpus

The AraBertMo_base_V2 model was pre - trained on ~3 million words:

• OSCAR - Arabic version "unshuffled_deduplicated_ar".

Training Results

This model achieves the following results:

Model Usage

You can use this model by initializing it as shown in the code example in the "Quick Start" section.

Research Background

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

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

💻 Usage Examples

Basic Usage

from transformers import AutoTokenizer, AutoModel
tokenizer = AutoTokenizer.from_pretrained("Ebtihal/AraBertMo_base_V2")
model = AutoModelForMaskedLM.from_pretrained("Ebtihal/AraBertMo_base_V2")

📄 License

No license information provided in the original document.

Additional Information

• Language: Arabic
• 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 "