I’ve put together a simple package to train an adapter matrix to fine-tune your embeddings to a new context. This includes OpenAI’s embedding models.
You’ll need the embeddings of the query-document pairs, and a label on whether the document is relevant to the query or not.
The idea is to have a simple and familiar api.
from embedding_adapter import EmbeddingAdapter
adapter = EmbeddingAdapter()
adapter.fit(query_embeddings, document_embeddings, labels)
More details in the repo’s README.
Any feedback would be most appreciated