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Description
Created Scala and Python classes for the BGE Embeddings models.
Motivation and Context
Spark NLP currently supports BGE embeddings but didn't have a specific class to store and work with those models. The current approach is to load the models as BertEmbeddings, which loads the sentence embeddings model, BGE, as word embeddings. To load the model as sentence embeddings, I added a new class based on the current E5 embeddings annotator.
How Has This Been Tested?
The code has not been tested, as I don't have a Scala environment set yet.
Screenshots (if appropriate):
Types of changes
Checklist: