Filling masked tokens in Arabic text, particularly in contexts enriched with knowledge from KGs.
Can be further fine-tuned for Arabic NLP tasks that require semantic understanding, such as text classification or question answering.
1from transformers import pipeline
2fill_mask = pipeline("fill-mask", model="AfnanTS/ARBERTv2_ArLAMA")
3fill_mask("اللغة [MASK] مهمة جدا."
Trained on the ArLAMA dataset, which is designed to represent Knowledge Graphs in natural language.
Continued pre-training of ArBERTv2 using Masked Language Modeling (MLM) tasks, integrating structured knowledge from Knowledge Graphs.