Sentence Similarity
sentence-transformers
Safetensors
Greek
English
ministral3
greek
english
retrieval
rag
embeddings
nemotron
Eval Results (legacy)
Instructions to use KIEFERSA/Sophea-Nemo-Embedding with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use KIEFERSA/Sophea-Nemo-Embedding with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("KIEFERSA/Sophea-Nemo-Embedding") 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": "2.11.0+cu128", | |
| "sentence_transformers": "5.6.0", | |
| "transformers": "5.13.0" | |
| }, | |
| "default_prompt_name": null, | |
| "model_type": "SentenceTransformer", | |
| "prompts": { | |
| "anchor": "query: ", | |
| "negative_1": "passage: ", | |
| "negative_2": "passage: ", | |
| "negative_3": "passage: ", | |
| "negative_4": "passage: ", | |
| "negative_5": "passage: ", | |
| "negative_6": "passage: ", | |
| "negative_7": "passage: ", | |
| "positive": "passage: " | |
| }, | |
| "similarity_fn_name": "cosine" | |
| } |