NAMAA-Space
/

GATE-Reranker-V1

Text Classification

sentence-transformers

Inference Endpoints

Model card Files Files and versions Community

omarelshehy commited on 4 days ago

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@@ -19,7 +19,7 @@ This model is designed to **improve search relevance** of **arabic** documents b
 ## Key Features 🔑
-- **Optimized for Arabic**: Built with rich Arabic data, this model understands both Modern Standard Arabic (MSA) and diverse dialects, making it highly effective across various Arabic-speaking regions.
 - **Advanced Document Ranking**: Ranks results with precision, perfect for search engines, recommendation systems, and question-answering applications.
 - **State-of-the-Art Performance**: Achieves excellent performance compared to famous rerankers(See [Evaluation](https://huggingface.co/NAMAA-Space/GATE-Reranker-V1#evaluation)), ensuring reliable relevance and precision.
@@ -47,4 +47,4 @@ scores = model.predict([(Query, Paragraph1), (Query, Paragraph2)])
 ## Evaluation

 ## Key Features 🔑
+- **Optimized for Arabic**: Built on the highly performant [Omartificial-Intelligence-Space/GATE-AraBert-v1](Omartificial-Intelligence-Space/GATE-AraBert-v1) with exclusivly rich Arabic data.
 - **Advanced Document Ranking**: Ranks results with precision, perfect for search engines, recommendation systems, and question-answering applications.
 - **State-of-the-Art Performance**: Achieves excellent performance compared to famous rerankers(See [Evaluation](https://huggingface.co/NAMAA-Space/GATE-Reranker-V1#evaluation)), ensuring reliable relevance and precision.
 ## Evaluation
+We evalute out model on