• fastNLP
• • Requirements
  • Resources
  • Installation
  • Models
  • Project Structure

fastNLP

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:

Requirements

• Python>=3.6
• numpy>=1.14.2
• torch>=0.4.0
• tensorboardX
• tqdm>=4.28.1

Resources

• Tutorials
• Documentation
• Source Code

Installation

Run the following commands to install fastNLP package.

pip install fastNLP

Models

fastNLP implements different models for variant NLP tasks.
Each model has been trained and tested carefully.

Check out models' performance, usage and source code here.

• Documentation
• Source Code

Project Structure

fastNLP	an open-source NLP library
fastNLP.api	APIs for end-to-end prediction
fastNLP.core	data representation & train/test procedure
fastNLP.models	a collection of NLP models
fastNLP.modules	a collection of PyTorch sub-models/components/wheels
fastNLP.io	readers & savers