com.microsoft.onnxruntime:onnxruntime-mobile
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The ONNX Runtime Mobile package is a size optimized inference library for executing ONNX (Open Neural Network Exchange) models on Android. This package is built from the open source inference engine but with reduced disk footprint targeting mobile platforms. To minimize binary size this library supports a reduced set of operators and types aligned to typical mobile applications. The ONNX model must be converted to ORT format in order to use it with this package. See https://onnxruntime.ai/docs/reference/ort-format-models.html for more details.
Readme
ONNX Runtime is a cross-platform inference and training machine-learning accelerator.
ONNX Runtime inference can enable faster customer experiences and lower costs, supporting models from deep learning frameworks such as PyTorch and TensorFlow/Keras as well as classical machine learning libraries such as scikit-learn, LightGBM, XGBoost, etc. ONNX Runtime is compatible with different hardware, drivers, and operating systems, and provides optimal performance by leveraging hardware accelerators where applicable alongside graph optimizations and transforms. Learn more →
ONNX Runtime training can accelerate the model training time on multi-node NVIDIA GPUs for transformer models with a one-line addition for existing PyTorch training scripts. Learn more →
General Information: onnxruntime.ai
Usage documentation and tutorials: onnxruntime.ai/docs
YouTube video tutorials: youtube.com/@ONNXRuntime
Companion sample repositories:
| System | Inference | Training |
|---|---|---|
| Windows | ||
| Linux | ||
| Mac | ||
| Android | ||
| iOS | ||
| Web | ||
| Other |
| System | Inference | Training |
|---|---|---|
| Linux |  |
Windows distributions of this project may collect usage data and send it to Microsoft to help improve our products and services. See the privacy statement for more details.
We welcome contributions! Please see the contribution guidelines.
For feature requests or bug reports, please file a GitHub Issue.
For general discussion or questions, please use GitHub Discussions.
This project has adopted the Microsoft Open Source Code of Conduct. For more information see the Code of Conduct FAQ or contact opencode@microsoft.com with any additional questions or comments.
This project is licensed under the MIT License.
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We found that com.microsoft.onnxruntime:onnxruntime-mobile demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 0 open source maintainers collaborating on the project.
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