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-hn with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use Sathvik0101/srag-biencoder-hn with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("Sathvik0101/srag-biencoder-hn") sentences = [ "My partner has made a serious mistake that has deeply hurt our relationship. I feel immense anger and betrayal, but also a deep love. I'm caught between forgiving them to save the relationship or protecting myself by walking away, and I don't know which choice will bring me peace.", "hṛṣīkeśaṃ tadā vākyam idam āha mahīpate | senayor ubhayor madhye rathaṃ sthāpaya me 'cyuta ||21|| yāvad etān nirīkṣe 'haṃ yoddhukāmān avasthitān | kair mayā saha yoddhavyam asmin raṇasamudyame ||22|| yotsyamānān avekṣe 'haṃ ya ete 'tra samāgatāḥ | dhārtarāṣṭrasya durbuddher yuddhe priyacikīrṣavaḥ ||23||", "na caitad vidmaḥ kataran no garīyo yad vā jayema yadi vā no jayeyuḥ | yān eva hatvā na jijīviṣāmas te 'vasthitāḥ pramukhe dhārtarāṣṭrāḥ ||6||", "suhṛn-mitrāry-udāsīna-madhyastha-dveṣya-bandhuṣu | sādhuṣv api ca pāpeṣu sama-buddhir viśiṣyate ||9||", "samaḥ śatrau ca mitre ca tathā mānāpamānayoḥ | śītoṣṇa-sukha-duḥkheṣu samaḥ saṅga-vivarjitaḥ ||18|| tulya-nindā-stutir maunī saṃtuṣṭo yena kenacit | aniketaḥ sthira-matir bhaktimān me priyo naraḥ ||19||", "kārpaṇya-doṣopahata-svabhāvaḥ pṛcchāmi tvāṃ dharma-saṃmūḍha-cetāḥ | yac chreyaḥ syān niścitaṃ brūhi tan me śiṣyas te 'haṃ śādhi māṃ tvāṃ prapannam ||7||", "aniṣṭam iṣṭaṃ miśraṃ ca trividhaṃ karmaṇaḥ phalam | bhavaty atyāgināṃ pretya na tu saṃnyāsināṃ kvacit ||12||", "samaḥ śatrau ca mitre ca tathā mānāpamānayoḥ | śītoṣṇa-sukha-duḥkheṣu samaḥ saṅga-vivarjitaḥ ||18|| tulya-nindā-stutir maunī saṃtuṣṭo yena kenacit | aniketaḥ sthira-matir bhaktimān me priyo naraḥ ||19||", "nirmāna-mohā jita-saṅga-doṣā adhyātma-nityā vinivṛtta-kāmāḥ | dvandvair vimuktāḥ sukha-duḥkha-saṃjñair gacchanty amūḍhāḥ padam avyayaṃ tat ||5||" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [9, 9] - Notebooks
- Google Colab
- Kaggle