Sentence Similarity
sentence-transformers
Safetensors
Arabic
Persian
xlm-roberta
embeddings
retrieval
arabic
persian
fiqh
islamic-jurisprudence
cross-lingual
bge-m3
text-embeddings-inference
Instructions to use sadiqoon/fiqh-embed-ar-fa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use sadiqoon/fiqh-embed-ar-fa with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("sadiqoon/fiqh-embed-ar-fa") sentences = [ "هذا شخص سعيد", "هذا كلب سعيد", "هذا شخص سعيد جدا", "اليوم هو يوم مشمس" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ca699245a895d7dd50395858a20ef1c43777a5ae7684de335dc15335bafd6071
- Size of remote file:
- 17.1 MB
- SHA256:
- f933516ee06b8509219a550c644897078ec4a225e5683f81c30b4c86c407821e
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