Feature Extraction
sentence-transformers
Safetensors
English
modernvbert
sparse-retrieval
splade
visual-document-retrieval
multimodal
information-retrieval
inference-free
sparse-encoder
custom_code
Instructions to use naver/v-splade-efficient with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use naver/v-splade-efficient with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("naver/v-splade-efficient", trust_remote_code=True) 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: 183 Bytes
b7836ce | 1 2 3 4 5 6 7 8 9 10 | {
"__version__": {
"sentence_transformers": "5.6.0",
"transformers": "5.13.0",
"pytorch": "2.10.0"
},
"model_type": "SparseEncoder",
"similarity_fn_name": "dot"
}
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