trt-torch-quickstart
OfficialQuickstart for compiling PyTorch models to TensorRT engines with torch_tensorrt.
AuthorNVIDIA
Version1.0.0
Installs0
System Documentation
What problem does it solve?
This Skill addresses the issue of converting PyTorch models to TensorRT engines efficiently using the torch_tensorrt library, providing a streamlined process for AI inference acceleration.
Core Features & Use Cases
- PyTorch to TensorRT Conversion: Offers both AOT (Ahead-of-Time) and JIT (Just-In-Time) compilation methods for PyTorch models.
- Model Prerequisites: Provides clear instructions for model requirements and environment setup to ensure successful compilation.
- Use Case: Ideal for users who wish to compile PyTorch models to TensorRT engines for AI inference without the need for an ONNX intermediate file.
Quick Start
Run the command: trt-torch-quickstart compile --model-path /path/to/your/model.py.
Dependency Matrix
Required Modules
torchtorch_tensorrttensorrt
Components
scriptsreferences
💻 Claude Code Installation
Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.
Please help me install this Skill: Name: trt-torch-quickstart Download link: https://github.com/NVIDIA/TensorRT/archive/main.zip#trt-torch-quickstart Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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