Instructions to use NAMAA-Space/zarra with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Model2Vec
How to use NAMAA-Space/zarra with Model2Vec:
from model2vec import StaticModel model = StaticModel.from_pretrained("NAMAA-Space/zarra") - sentence-transformers
How to use NAMAA-Space/zarra with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("NAMAA-Space/zarra") 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:
- 569a28d6a2673ea5e44b1c7415b0b7090f5cab1bb4ab3b43f1033c0d5f9cfeaa
- Size of remote file:
- 17.1 MB
- SHA256:
- e50d57f2617dfe4425aa46562197e4953b6f10875ed63c32f1859a91fa544170
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