Intel Deep Learning Deployment Toolkit //free\\ -

pip install openvino Assume you have an ONNX export of your PyTorch model:

mo --input_model my_model.onnx --output_dir ./optimized_model Here is a Python snippet to run your newly minted IR model: intel deep learning deployment toolkit

Take your slowest production model, run it through the Model Optimizer, and benchmark the result. You will be shocked. Have you used OpenVINO or the Intel DLDT in production? Let me know your latency improvements in the comments below! pip install openvino Assume you have an ONNX

Ditch the Complexity: Supercharge Inference with the Intel Deep Learning Deployment Toolkit Let me know your latency improvements in the comments below

If you are deploying to CPUs (and let's be honest, 90% of inference still happens on CPUs), you are leaving performance on the table by not using DLDT.

What if I told you that your existing Intel Xeon CPUs (or even your Core i5 laptop) are hiding a massive amount of untapped performance? The secret isn't buying new hardware; it's using the .