TensorRT
NVIDIA® TensorRT™ is an SDK for high-performance deep learning inference on NVIDIA GPUs. This repository contains the open source components of TensorRT.
Run deep learning models efficiently on NVIDIA graphics cards to speed up AI tasks.
From the README
pip install tensorrt
- For the per-model support matrix across import paths (LLM, encoder-NLP, vision, audio, diffusion, multimodal), see Supported Models.
- For code contributions to TensorRT-OSS, please see our Contribution Guide and Coding Guidelines.
- For a summary of new additions and updates shipped with TensorRT-OSS releases, please refer to the Changelog.
- For business inquiries, please contact [email protected]
- For press and other inquiries, please contact Hector Marinez at [email protected]
Excerpts from the project README on GitHub. Copyright and licensing remain with the respective authors.
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TensorRT has 13.2k stars on GitHub. It has been forked 2.4k times. TensorRT is written mainly in C++. It has been in active development since 2019. TensorRT is available under the Apache-2.0 license. Its main topics are deep-learning, gpu-acceleration, inference, nvidia.
What is TensorRT?
NVIDIA® TensorRT™ is an SDK for high-performance deep learning inference on NVIDIA GPUs. This repository contains the open source components of TensorRT.
Is TensorRT open source?
TensorRT is an open-source project. It is released under the Apache-2.0 license.
Is TensorRT free?
Yes. TensorRT is free and open source — you can use, modify and self-host it.
What license does TensorRT use?
TensorRT is available under the Apache-2.0 license.
What language is TensorRT written in?
TensorRT is written mainly in C++.
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