Feature Extraction
sentence-transformers
PyTorch
English
distilbert
splade
query-expansion
document-expansion
bag-of-words
passage-retrieval
sparse-encoder
sparse
Instructions to use naver/splade_v2_max with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use naver/splade_v2_max with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("naver/splade_v2_max") 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
- Xet hash:
- e2ad0e4381ae06e9f9100b4ed45081d443c74dda22527695fd0d7b5f683a2147
- Size of remote file:
- 268 MB
- SHA256:
- 2353027ff7931a6d78bd24d970a5422b3a7c593111fe3849065889cbcdf93094
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