# Overview

Welcome to The Burn Book 👋

This book will help you get started with the Burn deep learning framework, whether you are an
advanced user or a beginner. We have crafted some sections for you:

- [Basic Workflow: From Training to Inference](./basic-workflow): We'll start with the fundamentals,
  guiding you through the entire workflow, from training your models to deploying them for
  inference. This section lays the groundwork for your Burn expertise.

- [Building Blocks](./building-blocks): Dive deeper into Burn's core components, understanding how
  they fit together. This knowledge forms the basis for more advanced usage and customization.

- [Performance - Good Practices](./performance/good-practices/): Tips for writing models and
  training code that make the most of hardware resources while avoiding common pitfalls that can
  slow down execution.

- [Custom Training Loop](./custom-training-loop.md): Gain the power to customize your training
  loops, fine-tuning your models to meet your specific requirements. This section empowers you to
  harness Burn's flexibility to its fullest.

- [Saving & Loading Models](./saving-and-loading.md): Learn how to save and load your trained
  models, including importing weights from PyTorch and SafeTensors formats.

- [ONNX Import](./onnx-import.md): Learn how to import ONNX models using the
  [burn-onnx](https://github.com/tracel-ai/burn-onnx) crate.

- [Models & Pre-Trained Weights](./models-and-pretrained-weights.md): Get started quickly with
  ready-to-use models and pre-trained weights.

- [Advanced](./advanced): Finally, venture into advanced topics, exploring Burn's capabilities at
  their peak. This section caters to those who want to push the boundaries of what's possible with
  Burn.

Throughout the book, we assume a basic understanding of deep learning concepts, but we may refer to
additional material when it seems appropriate.
