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55<h4 > Easily achieve the best inference performance for any PyTorch model on the NVIDIA platform. </h4 >
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77[ ![ Documentation] ( https://img.shields.io/badge/docs-master-brightgreen )] ( https://nvidia.github.io/Torch-TensorRT/ )
8- [ ![ pytorch] ( https://img.shields.io/badge/PyTorch-2.4 -green )] ( https://www.python .org/downloads/release/python-31013/ )
9- [ ![ cuda] ( https://img.shields.io/badge/CUDA-12.4 -green )] ( https://developer.nvidia.com/cuda-downloads )
8+ [ ![ pytorch] ( https://img.shields.io/badge/PyTorch-2.8 -green )] ( https://download.pytorch .org/whl/nightly/cu128 )
9+ [ ![ cuda] ( https://img.shields.io/badge/CUDA-12.8 -green )] ( https://developer.nvidia.com/cuda-downloads )
1010[ ![ trt] ( https://img.shields.io/badge/TensorRT-10.9.0-green )] ( https://github.com/nvidia/tensorrt-llm )
1111[ ![ license] ( https://img.shields.io/badge/license-BSD--3--Clause-blue )] ( ./LICENSE )
1212[ ![ linux_tests] ( https://github.com/pytorch/TensorRT/actions/workflows/build-test-linux.yml/badge.svg )] ( https://github.com/pytorch/TensorRT/actions/workflows/build-test-linux.yml )
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