Feature Extraction
sentence-transformers
PyTorch
English
bert
splade
sparse-encoder
sparse
text-embeddings-inference
Instructions to use naver/splade-v3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use naver/splade-v3 with sentence-transformers:
from sentence_transformers import SparseEncoder model = SparseEncoder("naver/splade-v3") queries = ["Which planet is known as the Red Planet?"] documents = [ "Venus is often called Earth's twin because of its similar size and proximity.", "Mars, known for its reddish appearance, is often referred to as the Red Planet.", "Jupiter, the largest planet in our solar system, has a prominent red spot.", ] query_embeddings = model.encode_query(queries) document_embeddings = model.encode_document(documents) similarities = model.similarity(query_embeddings, document_embeddings) print(similarities) - Inference
- Notebooks
- Google Colab
- Kaggle
SPLADE-Index python package: An ultra-fast search index for SPLADE sparse retrieval models
🚀 1
1
#8 opened about 1 year ago
by
rasyosef
Loading `naver/splade-v3` model from transformer python library results in `ModuleNotFoundError`
2
#7 opened over 1 year ago
by
sirfumi
Unable to load model in transformers pipeline
3
#4 opened almost 2 years ago
by
stanleyt18
Adding `safetensors` variant of this model
#1 opened over 2 years ago
by
SFconvertbot