Currently, we have embeddings trained by ADA, stored in our vector db, we are planning to update the embedding model to text-embedding-small-1536.
Do we need to retrain our entire corpus due to a change of the embedding model?
We found that open AI uses the same tokeniser but both models ADA and text-embedding-small-1536 have different architecture.
if we create embedding from one model for the doc chunks and create embedding for another model for query chunks and use cosine similarity then how will cosine similarity play its role?
please assist…