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Improve documentation for PyTorch to ONNX and OpenVINO IR conversion … #3387

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22 changes: 20 additions & 2 deletions notebooks/convert-to-openvino/convert-to-openvino.ipynb
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"cell_type": "markdown",
"metadata": {},
"source": [
"Convert PyTorch model to ONNX format:"
"### Convert PyTorch Model to ONNX Format\n",
"/n",
"This step exports a trained PyTorch model into the ONNX (Open Neural Network Exchange) format.\n"
"\n"
"ONNX serves as an intermediate representation that enables interoperability between different deep learning frameworks and inference engines.\n"
"\n"
"The exported ONNX model can then be converted into OpenVINO Intermediate Representation (IR) format, which is optimized for efficient inference on supported hardware such as CPUs, GPUs, and edge devices."
]
},
{
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"## Conversion\n",
"[back to top ⬆️](#Table-of-contents:)\n",
"\n",
"To convert a model to OpenVINO IR, use the following API:"
"Convert the ONNX model to OpenVINO IR format:\n",
"\n",
"The convert_model() function transforms the ONNX model into OpenVINO's\n",
"\n",
"Intermediate Representation (IR), which is optimized for efficient inference.\n",
"\n",
"The IR format consists of two files:\n",
"\n",
"- XML file: defines the model architecture\n",
"\n",
"- BIN file: contains the model weights\n",
"\n",
"This representation improves performance on and reduces inference latency CPU and edge devices."
]
},
{
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