Daniel Voigt Godoy - Deep Learning with PyTorch Step-by-Step A Beginner’s Guide-leanpub

Chapter 11
Down the Yellow Brick Rabbit Hole
Spoilers
In this chapter, we will:
• learn about many useful packages for natural language processing (NLP):
NLTK, Gensim, flair, and HuggingFace
• build our own dataset from scratch using HuggingFace’s Dataset
• use different tokenizers on our dataset
• learn and load word embeddings using Word2Vec and GloVe
• train many models using embeddings in different ways
• use ELMo and BERT to retrieve contextual word embeddings
• use HuggingFace’s Trainer to fine-tune BERT
• fine-tune GPT-2 and use it in a pipeline to generate text
Jupyter Notebook
The Jupyter notebook corresponding to Chapter 11 [156] is part of the official Deep
Learning with PyTorch Step-by-Step repository on GitHub. You can also run it
directly in Google Colab [157] .
If you’re using a local installation, open your terminal or Anaconda prompt and
navigate to the PyTorchStepByStep folder you cloned from GitHub. Then, activate
the pytorchbook environment and run jupyter notebook:
$ conda activate pytorchbook
(pytorchbook)$ jupyter notebook
If you’re using Jupyter’s default settings, this link should open Chapter 11’s
notebook. If not, just click on Chapter11.ipynb in your Jupyter’s home page.
880 | Chapter 11: Down the Yellow Brick Rabbit Hole