I'm trying to use the text expansion query to implement semantic search on a rank features field. I've read the ELSER documentation and understand the process. I'm using a local/downloaded elasticsearch on docker (not connected to elastic cloud).
In this example they reference the ELSER model ID to query a rank features field:
I'm curious if there's a way to use this query but use a self deployed model (not on elastic cloud) rather than the ELSER model.
I'd start with Import the trained model and vocabulary | Machine Learning in the Elastic Stack [8.9] | Elastic on how to import custom NLP models (with
--url instead of
PS: Out of interest, which model do you have in mind?
You can import your own text embedding model into elasticsearch with eland and use query_vector_builder to embed your query.
This notebook is also an end to end example of how you would do this with a hugging face model https://github.com/elastic/elasticsearch-labs/blob/main/notebooks/integrations/hugging-face/loading-model-from-hugging-face.ipynb
Hope this helps!
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