I made a way to migrate between embedding models without re-embedding your entire corpus

This story is from 2026-09-10. It is preserved in the archive; the latest stories are on the live feed.

So I was playingw ith embedding models I saw that when you upgrade from model A to B, you face a very big backfilling cost Ie, suppose you have a 1b vectors from model A, and then you want to use model B. This would mean you have to re-embed all of your documents with model B before you can even se…

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Timeline · 4 reports

1. 2026-09-10 06:03 · r/learnmachinelearning
   I made a way to migrate between embedding models without re-embedding your entire corpus
2. 2026-09-10 00:14 · r/MachineLearning
   I made a way to migrate between embedding models without re-embedding your entire corpus [R]
3. 2026-09-10 00:12 · r/deeplearning
   I made a way to migrate between embedding models without re-embedding your entire corpus
4. 2026-09-10 00:10 · r/LocalLLaMA
   I made a way to migrate between embedding models without re-embedding your entire corpus