ONNX version of sentence-transormers/all-mpnet-base-v2

This is a sentence-transformers model: It maps sentences & paragraphs to a 384 dimensional dense vector space and can be used for tasks like clustering or semantic search. The ONNX version of this model is made for the Metarank re-ranker to do semantic similarity.

Check out the main Metarank docs on how to configure it.

TLDR:

- type: field_match
  name: title_query_match
  rankingField: ranking.query
  itemField: item.title
  distance: cos 
  method:
    type: bert 
    model: metarank/all-mpnet-base-v2

Building the model

$> pip install -r requirements.txt
$> python convert.py

============= Diagnostic Run torch.onnx.export version 2.0.0+cu117 =============
verbose: False, log level: Level.ERROR
======================= 0 NONE 0 NOTE 0 WARNING 0 ERROR ========================

License

Apache 2.0