Omartificial-Intelligence-Space/Arabic-mpnet-base-all-nli-triplet
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Arabic Matryoshka Embedding Models
A collection of advanced Arabic Matryoshka Embedding Models designed for efficient and high-performance Arabic NLP, available publicly on Hugging Face
Note This model is an English fine-tuned version derived from the "tomaarsen/mpnet-base-all-nli-triplet", which itself is originally based on "microsoft/mpnet-base". Despite being primarily trained on English data and having seen only a few Arabic tokens, this model has demonstrated impressive performance in Arabic NLP tasks. After fine-tuning, it achieved a notable score of 79.9 on the STS17 MTEB leaderboard.
Omartificial-Intelligence-Space/Arabic-all-nli-triplet-Matryoshka
Sentence Similarity • Updated • 1.37k • 1Note This model is fine-tuned from the "sentence-transformers/paraphrase-multilingual-mpnet-base-v2". It has been specifically adapted to handle Arabic NLP tasks, making it a powerful tool for understanding and processing Arabic text. On the MTEB STS17 leaderboard, it achieved an impressive score of 82.4. It is really powerful model for sentence similarty
Omartificial-Intelligence-Space/Arabert-all-nli-triplet-Matryoshka
Sentence Similarity • Updated • 1.33k • 4Note Leading the MTEB leaderboard, this model achieved a remarkable score of 83.16 on the STS17 MTEB leaderboard. It is fine-tuned from the powerful AraBERT architecture, specifically designed to handle Arabic language nuances. This model is highly recommended for tasks requiring precise semantic similarity and textual entailment in Arabic, showcasing its superiority in performance and reliability for Arabic NLP tasks.
Omartificial-Intelligence-Space/Arabic-labse-Matryoshka
Sentence Similarity • Updated • 1.29k • 2Note This sentence-transformers model, fine-tuned from sentence-transformers/LaBSE, has secured the second position on the STS17 MTEB leaderboard with a score of 82.47. It combines the strengths of LaBSE with the specific needs of Arabic language processing, making it a robust choice for tasks that require accurate semantic similarity and textual entailment in Arabic. This model is ideal for applications needing high performance and precision in understanding Arabic text.
Omartificial-Intelligence-Space/Marbert-all-nli-triplet-Matryoshka
Sentence Similarity • Updated • 1.13k • 1Note This model, fine-tuned from the MarBERT base, has achieved the fourth position on the STS17 MTEB leaderboard with a score of 82.18. It leverages the MarBERT architecture, which is specifically designed for Arabic language processing, enhancing its performance through Matryoshka fine-tuning.
Omartificial-Intelligence-Space/Arabic-MiniLM-L12-v2-all-nli-triplet
Sentence Similarity • Updated • 1.24k • 3Note This model, Omartificial-Intelligence-Space/Arabic-MiniLM-L12-v2-all-nli-triplet, fine-tuned from the sentence-transformers/paraphrase-multilingual-MiniLM-L12-v2 base, has achieved a commendable score of 81.11 on the STS17 MTEB leaderboard.