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
| [ | |
| { | |
| "idx": 0, | |
| "name": "0", | |
| "path": "", | |
| "type": "sentence_transformers.base.modules.transformer.Transformer" | |
| }, | |
| { | |
| "idx": 1, | |
| "name": "1", | |
| "path": "1_Pooling", | |
| "type": "sentence_transformers.sentence_transformer.modules.pooling.Pooling" | |
| }, | |
| { | |
| "idx": 2, | |
| "name": "2", | |
| "path": "2_Normalize", | |
| "type": "sentence_transformers.sentence_transformer.modules.normalize.Normalize" | |
| } | |
| ] |