Transformers Notebooks

This repository contains the example code from our O'Reilly book Natural Language Processing with Transformers:

<img alt="book-cover" height=200 src="images/book_cover.jpg" id="book-cover"/>

Getting started

You can run these notebooks on cloud platforms like Google Colab or your local machine. Note that most chapters require a GPU to run in a reasonable amount of time, so we recommend one of the cloud platforms as they come pre-installed with CUDA.

Running on a cloud platform

To run these notebooks on a cloud platform, just click on one of the badges in the table below:

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| Chapter | Colab | Kaggle | Gradient | Studio Lab | |:--------------------------------------------|:----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------| | Introduction | | | | | | Text Classification | | | | | | Transformer Anatomy | | | | | | Multilingual Named Entity Recognition | | | | | | Text Generation | | | | | | Summarization | | | | | | Question Answering | | | | | | Making Transformers Efficient in Production | | | | | | Dealing with Few to No Labels | | | | [](https://studiolab.sagemaker.aws/import/github/nlp-with-transformers