In-depth tutorials and examples on LLM training and inference infrastructure, such as, Pytorch, Fairscale, Nvidia AI Modules (cuDNN, tensorRT, Megatron-LM), HuggingFace.

LLM tutorial materials include but not limited to NVIDIA NeMo, TensorRT-LLM, Triton Inference Server, and NeMo Guardrails.

Nvidia TensorRT tutorial examples

A tutorial for TensorRT overall pipeline optimization from ONNX, TensorFlow Frozen Graph, pth, UFF, or PyTorch TRT) framework.

A tutorial for TensorRT overall pipeline optimization from ONNX, TensorFlow Frozen Graph, pth, UFF, or PyTorch TRT) framework.

Simple ptq/qat workflow, based on https://github.com/NVIDIA/TensorRT/blob/release/10.2/quickstart/quantization_tutorial/qat-ptq-workflow.ipynb

Tutorial repository to compile Tensorflow in NVIDIA Jetson Nano with Jetpack 6.0, CUDA 12.2, cuDNN 8.9, and TensorRT 8.6 to use Tensorflow C API.

This repository serves as a comprehensive guide for beginners to learn and explore NVIDIA TensorRT. It includes practical code examples, step-by-step tutorials, and explanations of TensorRT's key features. Topics covered include custom operators, optimization techniques, and real-world use cases.