🚀 𝗕𝘂𝗶𝗹𝗱𝗶𝗻𝗴 𝗮 𝗖𝘂𝘀𝘁𝗼𝗺 𝗔𝗿𝗮𝗯𝗶𝗰 𝗦𝗲𝗺𝗮𝗻𝘁𝗶𝗰 𝗦𝗲𝗮𝗿𝗰𝗵 𝗠𝗼𝗱𝗲𝗹 𝘄𝗶𝘁𝗵 𝗔𝗿𝗮𝗯𝗶𝗰 𝗠𝗮𝘁𝗿𝘆𝗼𝘀𝗵𝗸𝗮 𝗘𝗺𝗯𝗲𝗱𝗱𝗶𝗻𝗴𝘀 𝗳𝗼𝗿 𝗥𝗔𝗚 𝗨𝘀𝗶𝗻𝗴 𝗦𝗲𝗻𝘁𝗲𝗻𝗰𝗲 𝗧𝗿𝗮𝗻𝘀𝗳𝗼𝗿𝗺𝗲𝗿𝘀
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Omar Najar
Jul 12, 2024, 11:52:16 AMJul 12
to SIGARAB: Special Interest Group on Arabic Natural Language Processing
I'm excited to share my latest blog post on Medium! [ https://lnkd.in/dNiCE-Kc] 🎉
In this article, I delve into the process of creating a robust Arabic semantic search model using our innovative Arabic Matryoshka Embeddings. This model excels in Retrieval-Augmented Generation (RAG) applications, showcasing the power and potential of advanced NLP techniques tailored for the Arabic language.
🔍 𝗪𝗵𝗮𝘁 𝗬𝗼𝘂'𝗹𝗹 𝗟𝗲𝗮𝗿𝗻:
🔸 The fundamentals of semantic search and its application in Arabic NLP.
How to fine-tune Sentence Transformers for creating effective semantic search models.
🔸 The impressive performance of our Matryoshka Embedding models, which have achieved top ranks on the MTEB leaderboard.
🔸 Practical steps and code examples for implementing your own semantic search model.
🔸 Insights on the benefits of using local encoded data versus storing embeddings in a vector database.
This post is a comprehensive guide for anyone interested in enhancing their Arabic NLP capabilities and exploring the cutting-edge advancements in this field.
🔗 𝙍𝙚𝙖𝙙 𝙩𝙝𝙚 𝙛𝙪𝙡𝙡 𝙖𝙧𝙩𝙞𝙘𝙡𝙚 𝙤𝙣 𝙈𝙚𝙙𝙞𝙪𝙢
https://lnkd.in/dNiCE-Kc
In this article, I delve into the process of creating a robust Arabic semantic search model using our innovative Arabic Matryoshka Embeddings. This model excels in Retrieval-Augmented Generation (RAG) applications, showcasing the power and potential of advanced NLP techniques tailored for the Arabic language.
🔍 𝗪𝗵𝗮𝘁 𝗬𝗼𝘂'𝗹𝗹 𝗟𝗲𝗮𝗿𝗻:
🔸 The fundamentals of semantic search and its application in Arabic NLP.
How to fine-tune Sentence Transformers for creating effective semantic search models.
🔸 The impressive performance of our Matryoshka Embedding models, which have achieved top ranks on the MTEB leaderboard.
🔸 Practical steps and code examples for implementing your own semantic search model.
🔸 Insights on the benefits of using local encoded data versus storing embeddings in a vector database.
This post is a comprehensive guide for anyone interested in enhancing their Arabic NLP capabilities and exploring the cutting-edge advancements in this field.
🔗 𝙍𝙚𝙖𝙙 𝙩𝙝𝙚 𝙛𝙪𝙡𝙡 𝙖𝙧𝙩𝙞𝙘𝙡𝙚 𝙤𝙣 𝙈𝙚𝙙𝙞𝙪𝙢
https://lnkd.in/dNiCE-Kc
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