Sentence Similarity
sentence-transformers
Safetensors
modernbert
feature-extraction
dense
multilingual
code search
text-embeddings-inference
🇪🇺 Region: EU
Instructions to use lightonai/mDenseOn-unsupervised with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use lightonai/mDenseOn-unsupervised with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("lightonai/mDenseOn-unsupervised") sentences = [ "That is a happy person", "That is a happy dog", "That is a very happy person", "Today is a sunny day" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
Commit History
-
Update citation to arXiv paper and add arxiv tag
Paulo de Moura0c60b5b -
Update README.md
Verified signature5fc35cd -
Update README.md
Verified signatured0b986f
-
Initial commit
Co-authored-by: Paulo de Moura <Paulo de Moura@users.noreply.huggingface.co> Co-authored-by: NohTow <NohTow@users.noreply.huggingface.co> Co-authored-by: ameliechatelain <ameliechatelain@users.noreply.huggingface.co>b4009dd