Sentence Similarity
sentence-transformers
Safetensors
xlm-roberta
feature-extraction
Generated from Trainer
dataset_size:4858
loss:MultipleNegativesRankingLoss
text-embeddings-inference
Instructions to use Sathvik0101/srag-biencoder-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use Sathvik0101/srag-biencoder-v1 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("Sathvik0101/srag-biencoder-v1") sentences = [ "I've achieved a lot in my career, but I still feel a deep sense of emptiness. I thought reaching these milestones would bring lasting satisfaction, but it hasn't. Was it all for nothing? What is my true purpose if external achievements don't fulfill me?", "abhyāsa-yoga-yuktena cetasā nānya-gāminā | paramaṃ puruṣaṃ divyaṃ yāti pārthānucintayan ||8||", "abhyāse 'py asamartho 'si mat-karma-paramo bhava | mad-artham api karmāṇi kurvan siddhim avāpsyasi ||10||", "na kartṛtvaṃ na karmāṇi lokasya sṛjati prabhuḥ | na karma-phala-saṃyogaṃ svabhāvas tu pravartate ||14||" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle