{ "cells": [ { "cell_type": "markdown", "id": "da9fd6a8", "metadata": {}, "source": [ "# Getting Started\n", "\n", "## Overview\n", "\n", "Transformer Engine (TE) is a library for accelerating Transformer models on NVIDIA GPUs, providing better performance with lower memory utilization in both training and inference. It provides support for 8-bit floating point (FP8) precision on Hopper GPUs, implements a collection of highly optimized building blocks for popular Transformer architectures, and exposes an automatic-mixed-precision-like API that can be used seamlessy with your PyTorch code. It also includes a framework-agnostic C++ API that can be integrated with other deep learning libraries to enable FP8 support for Transformers.\n", "\n", "## Let's build a Transformer layer!\n", "\n", "