Solving Sentence Pair Tasks Using Simple Transformers
Want to use Transformers for Sentence Pair NLP tasks? Simple Transformers has you covered!
Preface
The Simple Transformers library is built on top of the excellent Transformers library by Hugging Face with the goal of making Transformer models quick and easy to use.
Introduction
Sentence pair tasks, as the name suggests, are Natural Language Processing (NLP) tasks where the input features consist of two pieces of text (not necessarily grammatical sentences). Textual entailment and semantic similarity are a couple of examples for such tasks.
Considering the unprecedented success of BERT and other Transformer models in many NLP tasks, it should come as no surprise that they excel at sentence pair tasks as well. This guide demonstrates how you can harness the power of Transformer models to solve Sentence Pair tasks using Simple Transformers.
All source code for Simple Transformers is available on the Github Repo. If you have any issues or questions, that’s the place to resolve them. Please do check it out!
Setup
- Install Anaconda or Miniconda Package Manager from here
