From ad3b59b11c641ac78314bf7dc003d6b6c0391842 Mon Sep 17 00:00:00 2001 From: Xipeng Qiu Date: Fri, 17 Aug 2018 00:05:33 +0800 Subject: [PATCH] Update README.md --- README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/README.md b/README.md index 6a8fa418..efa1b15b 100644 --- a/README.md +++ b/README.md @@ -5,7 +5,7 @@ fastNLP is a modular Natural Language Processing system based on PyTorch, for fast development of NLP tools. It divides the NLP model based on deep learning into different modules. These modules fall into 4 categories: encoder, interaction, aggregation and decoder, while each category contains different implemented modules. Encoder modules encode the input into some abstract representation, interaction modules make the information in the representation interact with each other, aggregation modules aggregate and reduce information, and decoder modules decode the representation into the output. Most current NLP models could be built on these modules, which vastly simplifies the process of developing NLP models. The architecture of fastNLP is as the figure below: -![](fastnlp-architecture.pdf) +![](https://github.com/fastnlp/fastNLP/raw/master/fastnlp-architecture.pdf) ## Requirements