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NOTE:
The number of mentions on this list indicates mentions on common posts plus user suggested alternatives.
Hence, a higher number means a better onnx-simplifier alternative or higher similarity.
onnx-simplifier reviews and mentions
Posts with mentions or reviews of onnx-simplifier.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2022-11-20.
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Show: Cross-platform Image segmentation on video using eGUI, onnxruntime and ffmpeg
onnx-simplifier can shed some of incompatibilities in widespread use, but is itself bug ridden and lagging behind the standard. For any serious model, or when you don't get lucky simplifying the model upstream, you'd generally want good support of opset 11.
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[Technical Article] OCR Upgrade
ONNX Simplifier：https://github.com/daquexian/onnx-simplifier
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PyTorch 1.10
As far as I know, the ONNX format won't give you a performance boost on its own. However, there are ONNX optimizers for the ONNX runtime which will speed up your inference.
But if you are using Nvidia Hardware, then TensorRT should give you the best performance possible, especially if you change the precision level. Don't forget to simplify your ONNX model before you converting it to TensorRT though: https://github.com/daquexian/onnx-simplifier
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A note from our sponsor - WorkOS
workos.com | 23 Apr 2024
Stats
Basic onnx-simplifier repo stats
3
3,546
7.1
14 days ago
daquexian/onnx-simplifier is an open source project licensed under Apache License 2.0 which is an OSI approved license.
The primary programming language of onnx-simplifier is C++.
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