Sentence Similarity
sentence-transformers
Safetensors
xlm-roberta
feature-extraction
Generated from Trainer
dataset_size:202149
loss:MultipleNegativesRankingLoss
Eval Results (legacy)
text-embeddings-inference
Instructions to use mjaliz/bslm-pair-206k with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use mjaliz/bslm-pair-206k with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("mjaliz/bslm-pair-206k") sentences = [ "کفش پاشنه سه سانتی", "گردنبند عقیق یمن کد 22060 با آویز بیضی شکل", "کفش پاشنهدار زنانه کلاسیک مشکی طرح سهبعدی پاشنه ۵ سانتیمتری مدل ۱۰۰۲", "تاب فلزی دو نفره طرح برج 90 سانتیمتری با رنگ روغنی" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
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