Sentence Similarity
sentence-transformers
Safetensors
English
mpnet
feature-extraction
generated
Eval Results (legacy)
text-embeddings-inference
Instructions to use tomaarsen/st-v3-test-mpnet-base-allnli-stsb with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use tomaarsen/st-v3-test-mpnet-base-allnli-stsb with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("tomaarsen/st-v3-test-mpnet-base-allnli-stsb") sentences = [ "Really? No kidding! ", "yeah really no kidding", "At the end of the fourth century was when baked goods flourished.", "The campaigns seem to reach a new pool of contributors." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
Ctrl+K