A library for efficient similarity search and clustering of dense vectors
Project description
Faiss is a library for efficient similarity search and clustering of dense
vectors. It contains algorithms that search in sets of vectors of any size,
up to ones that possibly do not fit in RAM. It also contains supporting
code for evaluation and parameter tuning. Faiss is written in C++ with
complete wrappers for Python/numpy. Some of the most useful algorithms
are implemented on the GPU. It is developed by Facebook AI Research.
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