| Metadata-Version: 2.1 |
| Name: faiss-gpu |
| Version: 1.7.2 |
| Summary: A library for efficient similarity search and clustering of dense vectors. |
| Home-page: https://github.com/kyamagu/faiss-wheels |
| Author: Kota Yamaguchi |
| Author-email: KotaYamaguchi1984@gmail.com |
| License: MIT |
| Keywords: search nearest neighbors |
| Platform: UNKNOWN |
| Classifier: Development Status :: 4 - Beta |
| Classifier: Intended Audience :: Developers |
| Classifier: Intended Audience :: Science/Research |
| Classifier: License :: OSI Approved :: MIT License |
| Classifier: Operating System :: MacOS :: MacOS X |
| Classifier: Operating System :: Microsoft :: Windows |
| Classifier: Operating System :: POSIX |
| Classifier: Programming Language :: Python :: 3.6 |
| Classifier: Programming Language :: Python :: 3.7 |
| Classifier: Programming Language :: Python :: 3.8 |
| Classifier: Programming Language :: Python :: 3.9 |
| Classifier: Programming Language :: Python :: 3.10 |
| Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence |
| License-File: LICENSE |
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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. It is developed by Facebook AI Research. |
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