Albert Xlarge Arabic
An Arabic version of the ALBERT Xlarge pretrained language model, trained on approximately 4.4 billion words, supporting Modern Standard Arabic and some dialectal content.
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Release Time : 3/2/2022
Model Overview
This model is the Arabic version of the ALBERT Xlarge architecture, primarily used for masked language modeling tasks, suitable for Arabic text processing and analysis.
Model Features
Multi-source Pretraining Data
Pretrained on OSCAR Arabic and Wikipedia data, totaling approximately 4.4 billion words.
Dialect Support
Includes not only Modern Standard Arabic but also some dialectal content.
TPU Training Optimization
Trained using Google's free TPU v3-8 with adjusted training parameters for improved efficiency.
Model Capabilities
Arabic Text Understanding
Masked Language Modeling Tasks
Named Entity Recognition (NER)
Use Cases
Natural Language Processing
Arabic Text Analysis
Used for analyzing Arabic text to understand semantics and context.
Named Entity Recognition
Identifies named entities in Arabic text, such as person names, locations, etc.
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