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: 241 Bytes
e5b0973 | 1 2 3 4 5 6 7 8 9 10 | {
"transformer_task": "feature-extraction",
"modality_config": {
"text": {
"method": "forward",
"method_output_name": "last_hidden_state"
}
},
"module_output_name": "token_embeddings"
} |