# Introduction

## Welcome to the 🤗 Course!

This course will teach you about natural language processing (NLP) using libraries from the Hugging Face ecosystem — 🤗 Transformers, 🤗 Datasets, 🤗 Tokenizers, and 🤗 Accelerate — as well as the Hugging Face Hub. It’s completely free and without ads.

## What to expect?

Here is a brief overview of the course:

• Chapters 1 to 4 provide an introduction to the main concepts of the 🤗 Transformers library. By the end of this part of the course, you will be familiar with how Transformer models work and will know how to use a model from the Hugging Face Hub, fine-tune it on a dataset, and share your results on the Hub!
• Chapters 5 to 8 teach the basics of 🤗 Datasets and 🤗 Tokenizers before diving into classic NLP tasks. By the end of this part, you will be able to tackle the most common NLP problems by yourself.
• Chapters 9 to 12 dive even deeper, showcasing specialized architectures (memory efficiency, long sequences, etc.) and teaching you how to write custom objects for more exotic use cases. By the end of this part, you will be ready to solve complex NLP problems and make meaningful contributions to 🤗 Transformers.

This course:

## Who are we?

• How to use the pipeline function to solve NLP tasks such as text generation and classification