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ce-msmarco-MiniLM-L6-v2
metarank/ce-msmarco-MiniLM-L6-v2
ce-msmarco-MiniLM-L6-v2 is a feature extraction model from metarank. Use it when you need embeddings to search or compare text. It is set up for sentence-transformers. The card lists the license as apache-2.0.
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 th…
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At a glance
- Task
- Feature Extraction
- Library
- sentence-transformers
- License
- apache-2.0
- Model type
- bert
- Access
- Public
- Created
- Apr 11, 2023
- Updated
- Dec 1, 2023
- SHA
- 1f86de4e
Model card
From the Hugging Face model README
ONNX version of cross-encoder/mcmarco-MiniLM-L6-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-MiniLM-L6-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
- Task
- Feature Extraction
- Library
- sentence-transformers
- Type
- bert
- License
- apache-2.0
- Languages
- en
- Created
- Apr 11, 2023
- Updated
- Dec 1, 2023