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As discussed in https://dmitry-kan.medium.com/speeding-up-bert-search-in-elasticsearch-750f1f34f455 the current configuration of ODFE allows indexing maximum 200k vectors.
The goal is to index 1M vectors to compare with all other KNN implementations.
The text was updated successfully, but these errors were encountered:
#11 optimized params to reach 700k vectors indexed (still not 1M)
97655bb
Feature/hnswlib (#24)
5a25783
* #9 fix for method typo * #3 docs for ODFE index configuration and hyper-parameters * #9 reqs freeze * #11 optimized params to reach 700k vectors indexed (still not 1M) * #16 indexer for hnswlib, stores randomly generated vectors into binary index on disk * #16 I/O for binary vector format from Yandex (image dataset) * #16 hnswlib indexer for big-ann * #16 vector data visualizer (tensorboard) * #17 NSW graph visualization * #17 NSW graph implementation * #17 pca and t-sne * #17 viz code (fbin->tsv) * #17 sharding * #17 sharding algorithm, first two steps * #17 sharding algorithm, first two steps * added toml config * added IDE path --------- Co-authored-by: dmitry.kan <[email protected]>
DmitryKey
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As discussed in https://dmitry-kan.medium.com/speeding-up-bert-search-in-elasticsearch-750f1f34f455 the current configuration of ODFE allows indexing maximum 200k vectors.
The goal is to index 1M vectors to compare with all other KNN implementations.
The text was updated successfully, but these errors were encountered: