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Torch-TensorRT Notebooks

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Collection of Jupyter Notebooks illustrating how Torch-TensorRT can optimize inference with several well-known deep learning models



Latest Version



April 4, 2023

Compressed Size

1.33 MB

Torch-TensorRT is an integration of the PyTorch deep learning framework and the TensorRT inference acceleration framework. With this toolkit, users can generate an optimized TensorRT engine from a trained PyTorch model with a single line of code. The tutorial notebooks included here illustrate the inference optimization procedure (and benchmark the results) for the following networks and applications:

  • Hugging Face BERT: Masked Language Modeling
  • EfficientNet: Image Classification
  • Resnet50: Image Classification
  • SSD: Object Detection