jp6/cu126/: faiss-1.7.4 metadata and description
A library for efficient similarity search and clustering of dense vectors
| author | Matthijs Douze, Jeff Johnson, Herve Jegou, Lucas Hosseini |
| author_email | matthijs@fb.com |
| keywords | search nearest neighbors |
| license | MIT |
| requires_dist |
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no releases from root/pypi are included.
| File | Tox results | History |
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faiss-1.7.4-py3-none-any.whl
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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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