# Zero to TorchForge: From RL Theory to Production-Scale Implementation

A comprehensive guide for ML Engineers building distributed RL systems for language models.

Some of the examples mentioned below will be conceptual in nature for understanding.
Please refer to [API Docs](./api) for more details.

Welcome to the Tutorials section! This section is inspired by the A-Z
PyTorch tutorial, shoutout to our PyTorch friends that remember!

## Tutorial Structure

This section currently is structured in 3 detailed parts:

1. [Part 1: RL Fundamentals - Using TorchForge Terminology](tutorials/zero-to-forge/1_RL_and_Forge_Fundamentals): This gives a quick refresher of Reinforcement Learning and teaches you TorchForge Fundamentals
2. [Part 2: Peeling Back the Abstraction - What Are Services?](tutorials/zero-to-forge/2_Forge_Internals): Goes a layer deeper and explains the internals of TorchForge
3. [Part 3: The TorchForge-Monarch Connection](tutorials/zero-to-forge/3_Monarch_101): It's a 101 to Monarch and how TorchForge Talks to Monarch

Each part builds upon the next and the entire section can be consumed in roughly an hour - Grab a Chai and Enjoy!

If you're eager, please checkout our SFT Tutorial too (Coming soon!)!

```{toctree}
:maxdepth: 1
:hidden:
tutorials/zero-to-forge/1_RL_and_Forge_Fundamentals
tutorials/zero-to-forge/2_Forge_Internals
tutorials/zero-to-forge/3_Monarch_101
```