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Embedding Dimension Selection
Guide to choosing optimal embedding dimensions balancing accuracy, storage costs, and computational requirements, covering Matryoshka embeddings and dimension reduction techniques.
Embedding Dimensionality
The size of vector embeddings, typically ranging from 384 to 4096 dimensions. Higher dimensions capture more information but increase storage, compute, and latency costs.
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