
How to Reduce Memory Requirements by up to 90%+ using Product Quantization
The details behind how you can compress vectors using PQ with little loss of recall!
September 19, 2023 · 16 min read
The details behind how you can compress vectors using PQ with little loss of recall!
Fine-tuning LlaMA 7B to use the Weaviate GraphQL APIs
Using the Weaviate Tile Encoder to compress vectors with Product Quantization.
Implementing HNSW + Product Quantization (PQ) vector compression in Weaviate.
Vector search on disks: How does Vamana compare to HNSW?
Self-Supervised Retrieval can surpass BM25 and Supervised techniques. This technique also pairs very well alongside BM25 in Hybrid Retrieval. Learn more about it.