安裝中文字典英文字典辭典工具!
安裝中文字典英文字典辭典工具!
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- ONNX Runtime | Home
import onnxruntime as ort # Load the model and create InferenceSession model_path = "path to your onnx model" session = ort InferenceSession(model_path) # "Load and preprocess the input image inputTensor" # Run inference outputs = session run(None, {"input": inputTensor}) print (outputs)
- Python | onnxruntime
Example to install onnxruntime-gpu for CUDA 11 *: python -m pip install onnxruntime-gpu --extra-index-url=https: aiinfra pkgs visualstudio com PublicPackages _packaging ort-cuda-11-nightly pypi simple
- Install ONNX Runtime | onnxruntime
Download the onnxruntime-android AAR hosted at MavenCentral, change the file extension from aar to zip, and unzip it Include the header files from the headers folder, and the relevant libonnxruntime so dynamic library from the jni folder in your NDK project
- ONNX Runtime | onnxruntime
ONNX Runtime for Inferencing ONNX Runtime Inference powers machine learning models in key Microsoft products and services across Office, Azure, Bing, as well as dozens of community projects
- Tutorials - onnxruntime
ONNX Runtime: cross-platform, high performance ML inferencing and training accelerator
- Get Started - onnxruntime
ONNX Runtime: cross-platform, high performance ML inferencing and training accelerator
- NVIDIA - CUDA | onnxruntime
To reduce the need for manual installations of CUDA and cuDNN, and ensure seamless integration between ONNX Runtime and PyTorch, the onnxruntime-gpu Python package offers API to load CUDA and cuDNN dynamic link libraries (DLLs) appropriately
- Web | onnxruntime
With onnxruntime-web, you have the option to use webgl, webgpu or webnn (with deviceType set to gpu) for GPU processing, and WebAssembly (wasm, alias to cpu) or webnn (with deviceType set to cpu) for CPU processing All ONNX operators are supported by WASM but only a subset are currently supported by WebGL, WebGPU and WebNN
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