Go beyond the basics and master vector search with Qdrant. Learn how to combine filtering, hybrid retrieval, multivectors, and reranking to build high-quality search.
Part 5 of the sparse embeddings series. We packaged the entire training pipeline from Parts 1-4 into an open-source CLI and web dashboard that fine-tunes SPLADE models for any product catalog in minutes.
Thierry Damiba
March 09, 2026
Part 4 of a 5-part series on fine-tuning SPLADE sparse embeddings for e-commerce search. Test cross-domain generalization, train a multi-domain model, and decide when to specialize vs generalize.
Thierry Damiba
March 09, 2026
Part 3 of a 5-part series on fine-tuning SPLADE sparse embeddings for e-commerce search. Index products in Qdrant, run retrieval benchmarks, and implement ANCE-inspired hard negative mining for a 28% improvement over BM25.
Thierry Damiba
March 09, 2026
Part 2 of a 5-part series on fine-tuning SPLADE sparse embeddings for e-commerce search. Build a training pipeline on Modal with persistent checkpoints, SpladeLoss, and hyperparameter sweeps.
Thierry Damiba
March 09, 2026
Part 1 of a 5-part series on fine-tuning SPLADE sparse embeddings for e-commerce search. Learn how sparse embeddings outperform BM25 and dense models for product search, how SPLADE works, and why Qdrant's native sparse vector support matters.
Thierry Damiba
March 09, 2026
Multi-vector representations are superior to single-vector embeddings in many benchmarks. MUVERA embeddings aim to solve the problem of slow multi-vector search by creating a single-vector representation that approximates the multi-vector representation. This single vector can be used for fast initial retrieval using traditional vector search methods, and then the multi-vector representation can be used for reranking the top results.
Kacper Łukawski
September 05, 2025
Learn everything about filtering in Qdrant. Discover key tricks and best practices to boost semantic search performance and reduce Qdrant's resource usage.
Sabrina Aquino, David Myriel
September 10, 2024
Our new Query API allows you to build a hybrid search system that uses different search methods to improve search quality & experience. Learn more here.
Kacper Łukawski
July 25, 2024
Discover the power of vector storage optimization and learn how to efficiently manage multiple vectors per object for enhanced semantic search capabilities.
Kacper Łukawski
October 05, 2022
Discover how to optimize your vector search capabilities with efficient batch search. Learn optimization strategies for faster, more accurate results.
Kacper Łukawski
September 26, 2022
