fastNLP documentation

A Modularized and Extensible Toolkit for Natural Language Processing. Currently still in incubation.

Introduction

FastNLP is a modular Natural Language Processing system based on PyTorch, built for fast development of NLP models.

A deep learning NLP model is the composition of three types of modules:

module type functionality example
encoder encode the input into some abstract representation embedding, RNN, CNN, transformer
aggregator aggregate and reduce information self-attention, max-pooling
decoder decode the representation into the output MLP, CRF

For example:

_images/text_classification.png

API Reference

If you are looking for information on a specific function, class or method, this part of the documentation is for you.

Indices and tables