Update README.md

README.md

@@ -11,7 +11,8 @@ pipeline_tag: fill-mask
 
 <img src="./arab_icon2.png" alt="Model Logo" width="30%" height="30%" align="right"/>
 
-The **ArBERTV2_EL** model is a transformer-based Arabic language model fine-tuned using the Entity Linking (EL) task. This model leverages Knowledge Graphs (KGs) for intrinsic evaluation of Masked Language Modeling (MLM) models without directly evaluating the EL model. The EL task ensures that the model benefits from the incorporation of structured knowledge during pre-training.
+**ArBERTV1_MLM** is a pre-trained Arabic language model fine-tuned using Masked Language Modeling (MLM) tasks. This model leverages Knowledge Graphs (KGs) to capture semantic relations in Arabic text, aiming to improve vocabulary comprehension and performance in downstream tasks.
+
 
 
 ## Uses
@@ -34,7 +35,7 @@ Can be further fine-tuned for Arabic NLP tasks that require semantic understandi
 
 ```python
 from transformers import pipeline
-fill_mask = pipeline("fill-mask", model="AfnanTS/ArBERTV2_EL")
+fill_mask = pipeline("fill-mask", model="AfnanTS/ARBERT_ArLAMA")
 fill_mask("اللغة [MASK] مهمة جدا."
 ```
 
@@ -48,4 +49,4 @@ Trained on the ArLAMA dataset, which is designed to represent Knowledge Graphs i
 
 ### Training Procedure
 
-Continued pre-training of the ArBERTv2 model using Entity Linking (EL) task.
+Continued pre-training of ArBERTv1 using Masked Language Modeling (MLM) to integrate KG-based knowledge.