Sentence Similarity
sentence-transformers
Safetensors
mpnet
feature-extraction
dataset_size:10K<n<100K
loss:CosineSimilarityLoss
text-embeddings-inference
Instructions to use JuanIgnacioSolerno/all-mpnet-base-v2-sts with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use JuanIgnacioSolerno/all-mpnet-base-v2-sts with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("JuanIgnacioSolerno/all-mpnet-base-v2-sts") sentences = [ "Tech Writer", "Tech Specialist", "Architectural Historian", "Order Selector (Picker)" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
Ctrl+K