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
File size: 518 Bytes
e5b0973 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 | {
"__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"
} |