Sentence Similarity
sentence-transformers
Safetensors
modernbert
feature-extraction
dense
multilingual
code search
text-embeddings-inference
🇪🇺 Region: EU
Instructions to use lightonai/mDenseOn with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use lightonai/mDenseOn with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("lightonai/mDenseOn") 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
File size: 299 Bytes
b7f8a04 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 | {
"__version__": {
"pytorch": "2.6.0+cu124",
"sentence_transformers": "5.4.1",
"transformers": "5.6.2"
},
"default_prompt_name": null,
"model_type": "SentenceTransformer",
"prompts": {
"document": "document: ",
"query": "query: "
},
"similarity_fn_name": "cosine"
} |