Feature Extraction
sentence-transformers
Safetensors
Arabic
eurobert
sentence-similarity
Generated from Trainer
dataset_size:2280319
loss:MatryoshkaLoss
loss:MultipleNegativesRankingLoss
Arabic
EuroBert
Semantic
custom_code
Eval Results (legacy)
Instructions to use Omartificial-Intelligence-Space/AraEuroBert-610M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use Omartificial-Intelligence-Space/AraEuroBert-610M with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("Omartificial-Intelligence-Space/AraEuroBert-610M", trust_remote_code=True) 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
- Xet hash:
- 12444c921ac45cecaa3eca943c4ed1978de3447d01d86ce692edf276b50b7ce4
- Size of remote file:
- 1.06 kB
- SHA256:
- 6e58fcedf896d19a9883358ca74c1348f8376ac1f23742aa86da8995964edb19
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