elasticsearch-labs
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Guides and examples for 2nd phase retrieval
Providing examples on how to re-rank using:
- bi-encoders and cross-encoders
- Learn to rank via feature extractors
- boosting on attributes like dates, popularity
Great suggestion.
Similar to how embedding pipelines can be added: https://www.elastic.co/guide/en/machine-learning/current/ml-nlp-text-emb-vector-search-example.html
or here:
https://www.elastic.co/search-labs/how-to-deploy-nlp-text-embeddings-and-vector-search
It would be cool to utilize the machine learning instance for re-ranking. Similarly, you could bring your own model via hugging face by installing it through the Eland Docker agent (as in the later link).
cc @joshdevins @leemthompo related to our conversation around guides and documentation for reranking
Yeah we should coordinate on this. We have some plans for documentation around this as well so let's make sure they are all talking about the same things.