PrithivirajDamodaran/SPLADERunner

Lite weight wrapper for the independent implementation of SPLADE++ models for search & retrieval pipelines. Models and Library created by Prithivi Da, For PRs and Collaboration checkout the readme.

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This tool helps improve search results by transforming text into a format that captures both exact keywords and broader meanings. It takes raw text, like a product description or a document, and processes it into a 'sparse representation' that can be used with search engines like Solr or Elasticsearch. This is ideal for anyone managing search functionality, such as e-commerce managers, content strategists, or knowledge base administrators, who want more relevant search outcomes.

No commits in the last 6 months. Available on PyPI.

Use this if you need to enhance the accuracy and relevance of your search or retrieval pipelines without the heavy computational demands of traditional semantic search methods.

Not ideal if you primarily rely on exact, keyword-only matching for your search needs and do not experience 'vocabulary mismatch' issues.

information-retrieval search-engine-optimization e-commerce-search knowledge-management content-discovery
No License Stale 6m
Maintenance 0 / 25
Adoption 7 / 25
Maturity 17 / 25
Community 6 / 25

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34

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2

Language

Python

License

Last pushed

Aug 24, 2024

Commits (30d)

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Dependencies

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