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Matryoshka Representation Learning
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Introduction to Matryoshka Embedding Models
This Hugging Face blog post introduces Matryoshka Representation Learning (MRL), a technique for training embedding models that encode information at multiple granularities within a single vector. The approach allows truncating embeddings to smaller dimensions without significant loss in retrieval quality, enabling flexible trade-offs between storage/compute costs and accuracy. The post covers training, evaluation, and practical usage of Matryoshka embedding models via the Sentence Transformers library.