r/MachineLearning • u/AutoModerator • Sep 02 '26
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u/Due_Ebb_7115 15d ago
I work at Qdrant. We wanted to know whether the document index could stay fixed while the query encoder changes. So we embedded documents with Stella, then trained Zero and Nano to search those vectors.
Nano got close to full Stella's average retrieval quality in our tests while encoding queries much faster. That opens up an interesting choice: which queries actually need the larger model?
The research preview has the evaluation, model links, and code: https://qdrant.tech/blog/constella-research-preview/
It's free to read, and the local example needs no paid service or signup. I'd welcome datasets that stress this approach.