4 ms·

rare words are out of vocab errors in vectors Especially if they aren’t in the token vocab

• mind-blight 3y ago
  Even worse, named entities vary from organization to organization. We have a client who uses a product called "Time". It's software time management. For that customer's documentation, time should be close to "product" and a bunch of other things that have nothing to do with the normal concept of time. I actually suspect that people would get a lot more bang for their buck fine tuning the embedding models on B2B datasets for their use case, rather than fine tuning an llm
  • Yacovlewis 3y ago
    Great example of how an entity like that could throw effective RAG out the window