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chasingegg 6218111233 Fix some typos (#3056) 
Summary: Pull Request resolved: https://github.com/facebookresearch/faiss/pull/3056

Reviewed By: pemazare

Differential Revision: D49617607

Pulled By: mlomeli1

fbshipit-source-id: b2d5df67e88e029882e697597af9f3fc8fe1e64c
2023-09-27 03:17:41 -07:00
..
CMakeLists.txt
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demo_auto_tune.py
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demo_client_server_ivf.py
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demo_imi_flat.cpp
Fix some typos (#3056)
2023-09-27 03:17:41 -07:00
demo_imi_pq.cpp
Fix some typos (#3056)
2023-09-27 03:17:41 -07:00
demo_ivfpq_indexing.cpp
fairring, faiss, fairness (4401366386162573988)
2023-09-14 00:50:50 -07:00
demo_nndescent.cpp
Put idx_t in the faiss namespace (#2582)
2022-11-30 08:25:30 -08:00
demo_ondisk_ivf.py
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demo_residual_quantizer.cpp
OSS legal requirements (#2698)
2023-02-07 14:32:56 -08:00
demo_sift1M.cpp
Put idx_t in the faiss namespace (#2582)
2022-11-30 08:25:30 -08:00
demo_weighted_kmeans.cpp
fairring, faiss, fairness (4401366386162573988)
2023-09-14 00:50:50 -07:00
README.md
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README.md

Demos for a few Faiss functionalities

demo_auto_tune.py

Demonstrates the auto-tuning functionality of Faiss

demo_ondisk_ivf.py

Shows how to construct a Faiss index that stores the inverted file data on disk, eg. when it does not fit in RAM. The script works on a small dataset (sift1M) for demonstration and proceeds in stages:

0: train on the dataset

1-4: build 4 indexes, each containing 1/4 of the dataset. This can be done in parallel on several machines

5: merge the 4 indexes into one that is written directly to disk (needs not to fit in RAM)

6: load and test the index