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:
- e83aaac29fd3cfbf115f082b99ca2607ed6c532d0feb9136efe7a105be3213a0
- Size of remote file:
- 264 kB
- SHA256:
- e3d2dd80a8be7bec0c3d3f9b89bc1b922c9d0d86e4ba8c35bd0353e6a4254b4e
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