Meet the Matryoshka Embedding Models that Produce Useful Embeddings of Various Dimensions

In the significantly developing field of Natural Language Processing (NLP), embedding models are essential for converting complicated items like text, images, and audio into numerical representations that computers can comprehend and interpret. These embeddings, which are essentially fixed-size dense vectors, form the basis for many different applications, such as clustering, recommendation systems, and similarity searches. […]

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