Welcome to TextPruner’s documentation
TextPruner is a toolkit for pruning pre-trained transformer-based language models written in PyTorch. It offers structured training-free pruning methods and a user-friendly interface.
The main features of TexPruner include:
Compatibility: TextPruner is compatible with different NLU pre-trained models. You can use it to prune your own models for various NLP tasks as long as they are built on the standard pre-trained models.
Usability: TextPruner can be used as a package or a CLI tool. They are both easy to use.
Efficiency: TextPruner reduces the model size in a simple and fast way. TextPruner uses structured training-free methods to prune models. It is much faster than distillation and other pruning methods that involve training.
TextPruner currently supports the following pre-trained models in transformers:
BERT
Albert
Electra
RoBERTa
XLM-RoBERTa
Installation
pip install textpruner
Note
This document is under development.