Feature Extraction
sentence-transformers
PyTorch
Safetensors
English
distilbert
splade
query-expansion
document-expansion
bag-of-words
passage-retrieval
knowledge-distillation
document encoder
sparse-encoder
sparse
asymmetric
text-embeddings-inference
Instructions to use naver/efficient-splade-V-large-query with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use naver/efficient-splade-V-large-query with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("naver/efficient-splade-V-large-query") 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] - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c84dafa6ecd2e52d0272dde19edf654140e9f54b459d34df999e0b4afac5db7b
- Size of remote file:
- 268 MB
- SHA256:
- e49bee82d42e607e335a478e408357a423f70decf20ad6a848bcc6441d013706
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