OnnxSlim can help you slim your onnx model, with less operators, but same accuracy, better inference speed.
- 🚀 2026/06/02: Achieved 10M downloads
- 🚀 2026/01/04: Achieved 5M downloads
- 🚀 2025/11/29: Top 1% on PyPI
- 🚀 2025/11/27: OnnxSlim is merged into NVIDIA TensorRT-Model-Optimizer 🤗🤗🤗
- 🚀 2025/05/17: OnnxSlim is merged into HuggingFace optimum 🤗🤗🤗
- 🚀 2025/04/30: Rank 1st in the AICAS 2025 LLM inference optimization challenge
- 🚀 2025/01/28: Achieved 1M downloads
- 🚀 2024/06/23: OnnxSlim is merged into transformers.js 🤗🤗🤗
- 🚀 2024/06/02: OnnxSlim is merged into ultralytics ❤️❤️❤️
- 🚀 2024/04/30: Rank 1st in the AICAS 2024 LLM inference optimization challenge held by Arm and T-head
- 🚀 2024/01/25: OnnxSlim is merged to mnn-llm, performance increased by 5%
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
Bash
onnxslim your_onnx_model slimmed_onnx_model
Inscript
import onnx
import onnxslim
model = onnx.load("model.onnx")
slimmed_model = onnxslim.slim(model)
if slimmed_model:
onnx.save(slimmed_model, "slimmed_model.onnx")
For more usage, see onnxslim -h or refer to our examples
Projects using OnnxSlim
References
Contributors
Contact
Discord: https://discord.gg/nRw2Fd3VUS QQ Group: 873569894
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