Sentence Similarity
sentence-transformers
Safetensors
bert
feature-extraction
Generated from Trainer
dataset_size:26
loss:MultipleNegativesRankingLoss
loss:MatryoshkaLoss
text-embeddings-inference
Instructions to use vineet10/new_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use vineet10/new_model with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("vineet10/new_model") sentences = [ "The Employee agrees to diligently, honestly, and to the best of their abilities, perform all", "What are the Payment Terms for the Batteries?", "What are the general obligations of the Employee?", "according to the MOU?" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
Ctrl+K