Sentence Similarity
sentence-transformers
ONNX
Safetensors
Morisyen
English
French
xlm-roberta
feature-extraction
mauritian-creole
kreol-morisien
matryoshka
mteb
Eval Results (legacy)
text-embeddings-inference
Instructions to use Singaraj/morisien-embed with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use Singaraj/morisien-embed with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("Singaraj/morisien-embed") sentences = [ "The weather is lovely today.", "It's so sunny outside!", "He drove to the stadium." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [3, 3] - Notebooks
- Google Colab
- Kaggle
| { | |
| "__version__": { | |
| "pytorch": "2.10.0+cu128", | |
| "sentence_transformers": "5.7.0", | |
| "transformers": "5.0.0" | |
| }, | |
| "default_prompt_name": null, | |
| "model_type": "SentenceTransformer", | |
| "prompts": { | |
| "document": "", | |
| "query": "" | |
| }, | |
| "similarity_fn_name": "cosine" | |
| } |