Downloads · 30 days
0
metarank/all-MiniLM-L6-v2
all-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…
Downloads · 30 days
0
Access
Public
Updated Sep 4, 2023
Repo size
274 MB
Likes
1
Public
Click a slice to open those files.
.onnx91 MB · 99%
From the Hugging Face model README
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
$> 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 ========================
Apache 2.0