Sentence Similarity
sentence-transformers
Safetensors
t5
feature-extraction
Generated from Trainer
dataset_size:3688
loss:MultipleNegativesRankingLoss
loss:CosineSimilarityLoss
custom_code
Eval Results (legacy)
Instructions to use Bharatdeep-H/pq_cache_6 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use Bharatdeep-H/pq_cache_6 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("Bharatdeep-H/pq_cache_6", trust_remote_code=True) sentences = [ "Am I invested in emerging markets?", "Do I have any investments in emerging markets?", "Do I have financials in my portfolio?", "Show me my recommendations" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
Ctrl+K