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

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 serve with the model, and on an H100, it would take ~108 days (qwen embed 8b, 106 docs/second). But I found an easier way to do it. The method is really simple; from the old index made with the source model, take K documents and rerank them with the new model. We see that when K is sufficient, the retr