Feature Extraction
sentence-transformers
PyTorch
ONNX
English
bert
splade++
document-expansion
sparse representation
bag-of-words
passage-retrieval
knowledge-distillation
document encoder
sparse-encoder
sparse
splade
text-embeddings-inference
Instructions to use seerware/Splade_PP_en_v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use seerware/Splade_PP_en_v2 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("seerware/Splade_PP_en_v2") 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:
- 9dc7416cc63ab105260f4fd35c077b7be87351d2097f6b2f64749f52b4becc9f
- Size of remote file:
- 470 kB
- SHA256:
- a792e24162d03958c23ea225d5d2d6907738443ae7f232c04530618394a9843d
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