Sentence Similarity
sentence-transformers
Safetensors
Arabic
gemma3_text
feature-extraction
dense
Generated from Trainer
dataset_size:1000000
loss:MatryoshkaLoss
loss:MultipleNegativesRankingLoss
arabic
Semantic
text-embeddings-inference
Instructions to use Omartificial-Intelligence-Space/AraGemma-Embedding-300m with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use Omartificial-Intelligence-Space/AraGemma-Embedding-300m with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("Omartificial-Intelligence-Space/AraGemma-Embedding-300m") sentences = [ "امرأة شقراء تطل على مشهد (سياتل سبيس نيدل)", "رجل يستمتع بمناظر جسر البوابة الذهبية", "فتاة بالخارج تلعب في الثلج", "شخص ما يأخذ في نظرة إبرة الفضاء." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
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