Sentence Similarity
sentence-transformers
Safetensors
English
modernbert
feature-extraction
dense
text-embeddings-inference
🇪🇺 Region: EU
Instructions to use lightonai/DenseOn-unsupervised with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use lightonai/DenseOn-unsupervised with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("lightonai/DenseOn-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
Download model.safetensors from lightonai/DenseOn-unsupervised: direct link, hf CLI and curl.
- Browser
- Download file 596 MB
-
https://huggingface.co/lightonai/DenseOn-unsupervised/resolve/main/model.safetensors
- Command line
-
hf download hf://lightonai/DenseOn-unsupervised/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/lightonai/DenseOn-unsupervised/resolve/main/model.safetensors
596 MB
- Xet hash:
- ed8dcb6d2b3526f6f9b1a06da5508e26092b3ecfda91f0c8474313a15da5d808
- Size of remote file:
- 596 MB
- SHA256:
- 87b1a9f9fe402bded82712e5e06c5d1425cbd5b5e9224d0365324e10812d3bc2
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