Building and Evaluating a WebApp for Effortless Deep Learning Model Deployment

In the field of deep learning, particularly Natural Language Processing (NLP), model deployment is a key process for public testing and analysis. However, developing a deployment pipeline is often difficult and time-consuming. To address this challenge, we developed SUD.DL, a web application to simplify the model deployment process for NLP researchers. Our application provides significant improvements in deployment efficiency, functionality discoverability, and deployment functionality, allowing NLP researchers to quickly deploy and test models on the web.