Hugging Face

Hugging Face is not new for us; Chapter 6, Transformers, introduced us to the library. Hugging Face is an NLP-centered startup, founded by Delangue and Chaumond in 2016. It has, in a short time, established itself as one of the best tools for all NLP-related tasks. The AutoNLP and accelerated inference API are available for a price. However, its core NLP libraries datasets, tokenizers, Accelerate, and transformers (Figure 16.1) are available for free. It has built a cool community-driven open-source platform.

Figure 16.1: NLP libraries from Hugging Face

The core of the Hugging Face ecosystem is its transformers library. The Tokenizers and Datasets libraries support the Transformers library. To use these libraries, we need to install them first. Transformers can be installed using a simple pip install command:

pip install transformers

Some of the out-of-the-box models available with Hugging Face are text summarization, question answering, text classification...