Awesome
OnnxSlim
<p align="center"> <a href="https://pypi.org/project/onnxslim"> <img src="https://badgen.net/pypi/v/onnxslim?color=blue" /> </a> <a href="https://pypi.org/project/onnxslim"> <img src="https://static.pepy.tech/badge/onnxslim/week" /> </a> <a href="https://pypi.org/project/onnxslim"> <img src="https://static.pepy.tech/badge/onnxslim/month" /> </a> <a href="https://pypi.org/project/onnxslim"> <img src="https://static.pepy.tech/badge/onnxslim" /> </a> <a href="https://github.com/inisis/onnxslim/actions/workflows/ci.yaml"> <img src="https://github.com/inisis/onnxslim/actions/workflows/ci.yml/badge.svg" /> </a> </p>OnnxSlim can help you slim your onnx model, with less operators, but same accuracy, better inference speed.
- 🚀 OnnxSlim is merged to mnn-llm, performance increased by 5%
- 🚀 Rank 1st in the AICAS 2024 LLM inference optimization challenge held by Arm and T-head
- 🚀 OnnxSlim is merged into ultralytics ❤️❤️❤️
- 🚀 OnnxSlim is merged into transformers.js 🤗🤗🤗
Installation
Using Prebuilt
pip install onnxslim
Install From Source
pip install git+https://github.com/inisis/OnnxSlim@main
Install From Local
git clone https://github.com/inisis/OnnxSlim && cd OnnxSlim/
pip install .
How to use
onnxslim your_onnx_model slimmed_onnx_model
<div align=left><img src="https://raw.githubusercontent.com/inisis/onnxslim/main/images/onnxslim.gif"></div>
For more usage, see onnxslim -h or refer to our examples
References
Contact
Discord: https://discord.gg/nRw2Fd3VUS QQ Group: 873569894