naver/splade-cocondenser-ensembledistil

feature extractionsentence-transformersensentence-transformerspytorchbertspladequery-expansiondocument-expansioncc-by-nc-sa-4.0
1.2M

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model = SparseEncoder("naver/splade-cocondenser-ensembledistil")

Run inference

queries = ["what causes aging fast"] documents = [ "UV-A light, specifically, is what mainly causes tanning, skin aging, and cataracts, UV-B causes sunburn, skin aging and skin cancer, and UV-C is the strongest, and therefore most effective at killing microorganisms. Again â\x80\x93 single words and multiple bullets.", "Answers from Ronald Petersen, M.D. Yes, Alzheimer's disease usually worsens slowly. But its speed of progression varies, depending on a person's genetic makeup, environmental factors, age at diagnosis and other medical conditions. Still, anyone diagnosed with Alzheimer's whose symptoms seem to be progressing quickly â\x80\x94 or who experiences a sudden decline â\x80\x94 should see his or her doctor.", "Bell's palsy and Extreme tiredness and Extreme fatigue (2 causes) Bell's palsy and Extreme tiredness and Hepatitis (2 causes) Bell's palsy and Extreme tiredness and Liver pain (2 causes) Bell's palsy and Extreme tiredness and Lymph node swelling in children (2 causes)", ] query_embeddings = model.encode_query(queries) document_embeddings = model.encode_document(documents) print(query_embeddings.shape, document_embeddings.shape)

[1, 30522] [3, 30522]

Get the similarity scores for the embeddings

similarities = model.similarity(query_embeddings, document_embeddings) print(similarities)

tensor([[ 9.9933, 10.8691, 3.4265]])


## Citation

If you use our checkpoint, please cite our work:

@misc{https://doi.org/10.48550/arxiv.2205.04733, doi = {10.48550/ARXIV.2205.04733}, url = {https://arxiv.org/abs/2205.04733}, author = {Formal, Thibault and Lassance, Carlos and Piwowarski, Benjamin and Clinchant, Stéphane}, keywords = {Information Retrieval (cs.IR), Computation and Language (cs.CL), FOS: Computer and information sciences, FOS: Computer and information sciences}, title = {From Distillation to Hard Negative Sampling: Making Sparse Neural IR Models More Effective}, publisher = {arXiv}, year = {2022}, copyright = {Creative Commons Attribution Non Commercial Share Alike 4.0 International} }

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