Feature Extraction
sentence-transformers
Safetensors
Arabic
eurobert
loss:MatryoshkaLoss
loss:MultipleNegativesRankingLoss
EuroBert
Arabic
custom_code
Eval Results (legacy)
Instructions to use Omartificial-Intelligence-Space/AraEuroBert-210M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use Omartificial-Intelligence-Space/AraEuroBert-210M with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("Omartificial-Intelligence-Space/AraEuroBert-210M", 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
| [ | |
| { | |
| "idx": 0, | |
| "name": "0", | |
| "path": "", | |
| "type": "sentence_transformers.models.Transformer" | |
| }, | |
| { | |
| "idx": 1, | |
| "name": "1", | |
| "path": "1_Pooling", | |
| "type": "sentence_transformers.models.Pooling" | |
| } | |
| ] |