faiss 1.7.2-6 source package in Ubuntu
Changelog
faiss (1.7.2-6) unstable; urgency=medium * Team upload. * Bump Standards-Version to 4.6.1 * Drop unneeded build depend on libblis3-serial (Closes: #1012595) -- Timo Röhling <email address hidden> Fri, 10 Jun 2022 17:37:14 +0200
Upload details
- Uploaded by:
- Debian Deep Learning Team
- Uploaded to:
- Sid
- Original maintainer:
- Debian Deep Learning Team
- Architectures:
- any
- Section:
- misc
- Urgency:
- Medium Urgency
See full publishing history Publishing
| Series | Published | Component | Section |
|---|
Downloads
| File | Size | SHA-256 Checksum |
|---|---|---|
| faiss_1.7.2-6.dsc | 2.0 KiB | efcb7d6ca13748f466abc2099d119d48796b09e7abffed12801711b403e94328 |
| faiss_1.7.2.orig.tar.gz | 723.1 KiB | d49b4afd6a7a5b64f260a236ee9b2efb760edb08c33d5ea5610c2f078a5995ec |
| faiss_1.7.2-6.debian.tar.xz | 6.4 KiB | 6c00d72a93a71ffea503611ccb153d0366e475cfbb2568314fc16f6f6c482055 |
Available diffs
- diff from 1.7.2-5 to 1.7.2-6 (594 bytes)
No changes file available.
Binary packages built by this source
- libfaiss-dev: efficient similarity search and clustering of dense vectors
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.
.
This package contains the CPU-only version of the development files.
- python3-faiss: Python 3 module for efficient similarity search and clustering of dense vectors
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.
.
This package contains the CPU-only version of the Python interface.
- python3-faiss-dbgsym: debug symbols for python3-faiss
