How to Build a Matryoshka-Optimized Sentence Embedding Model for Ultra-Fast Retrieval with 64-Dimension Truncation
In this tutorial, we fine-tune the embedding model of Sentence-Transformers using Matryoshka Representation Learning so that the initial vector measurements carry the most useful semantic signal. We train with MatryoshkaLoss on triplet data and verify the important promise of MRL by measuring the retrieval quality after truncating the embedding to 64, 128, and 256 dimensions. … Read more