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 config_sentence_transformers.json from lightonai/DenseOn-unsupervised: direct link, hf CLI and curl.
- Browser
- Download file 300 Bytes
-
https://huggingface.co/lightonai/DenseOn-unsupervised/resolve/main/config_sentence_transformers.json
- Command line
-
hf download hf://lightonai/DenseOn-unsupervised/config_sentence_transformers.json
-
curl -L -o config_sentence_transformers.json https://huggingface.co/lightonai/DenseOn-unsupervised/resolve/main/config_sentence_transformers.json
300 Bytes
| { | |
| "model_type": "SentenceTransformer", | |
| "__version__": { | |
| "sentence_transformers": "5.1.1", | |
| "transformers": "4.57.5", | |
| "pytorch": "2.9.0+cu128" | |
| }, | |
| "prompts": { | |
| "query": "query: ", | |
| "document": "document: " | |
| }, | |
| "default_prompt_name": null, | |
| "similarity_fn_name": "cosine" | |
| } |