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SENTENCE TRANSFORMERS

Embeddings and rerankers for semantic search and RAG

Apache-2.0

ABOUT

Building retrieval systems usually means stitching together separate embedding models, ranking logic, and training code, then tuning them for search quality and latency. Sentence Transformers packages state-of-the-art embedding and reranking models behind a consistent interface so teams can build semantic search and RAG pipelines without training custom representation models from scratch.

INSTALL
pip install -U sentence-transformers

INTEGRATION GUIDE

1. Generate dense embeddings for semantic search over documents, tickets, or product knowledge bases 2. Rerank retrieved passages before generation to improve answer quality in a RAG pipeline 3. Fine-tune embedding models on domain-specific pairs for legal, healthcare, or support search 4. Build duplicate detection, clustering, and recommendation systems from sentence-level embeddings

TAGS

embeddingsretrievalrerankingsemantic-searchragpythonhugging-face