## Introduction

The **Smol-Training Playbook** from Hugging Face is a comprehensive guide that distills best practices for training large language models (LLMs) on a relatively small compute budget. Central to this playbook are several specialized frameworks and libraries that make efficient training feasible. In this report, we examine the key tools imported or referenced in the playbook’s training pipeline – including **Nanotron**, **FlashAttention**, **Liger**, **DataTrove**, **TRL**, a...