Amr-Abdellatif/ONNX_Course_material
Repo explaining basic ways to use ONNX with different frameworks
This helps data scientists and machine learning engineers convert their AI models from various frameworks like PyTorch, TensorFlow, or Scikit-Learn into a standardized ONNX format. You provide an existing model, and it outputs a portable ONNX version, making it easier to deploy and optimize across different environments.
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Use this if you need to standardize your machine learning models for easier deployment, optimization, or to transfer them between different AI development tools.
Not ideal if you are looking for tools to train new machine learning models or for a low-code/no-code solution for model conversion.
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Jupyter Notebook
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Last pushed
Sep 20, 2024
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