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README.md

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-`gliner_arabic-v2.1_rich` is a specialized Named Entity Recognition (NER) model designed for processing Arabic text with high accuracy and robustness. Built on top of the `urchade/gliner_large-v2` base model, this version has been fine-tuned to excel in identifying a wide range of entities in Arabic, making it suitable for applications requiring rich entity extraction in Arabic-language datasets. The model also supports English to a limited extent, enabling cross-lingual use cases.
+`gliner_arabic-v2.1` is a specialized Named Entity Recognition (NER) model designed for processing Arabic text with high accuracy and robustness. Built on top of the `urchade/gliner_large-v2` base model, this version has been fine-tuned to excel in identifying a wide range of entities in Arabic, making it suitable for applications requiring rich entity extraction in Arabic-language datasets. The model also supports English to a limited extent, enabling cross-lingual use cases.
 
 This model is part of the **GLiNER** family, leveraging the Generalized Language-augmented Multimodal Entity Recognition framework to provide state-of-the-art performance in token classification tasks.