Fast vector similarity using Rust and Python
High-performance vector similarity library in Rust with Python bindings: Spearman, Kendall, distance correlation, Jensen-Shannon, Hoeffding's D, and bootstrapped confidence intervals. I recently found myself computing the similarity between lots of very high dimensional vectors (i.e., sentence embedding vectors from LLMs), and I wanted to try some more powerful measures of similarity/dependency than just Cosine similarity, which seems to be the default for everything nowadays bec.
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