adaptNMT is an open-source application that offers a streamlined approach to the development and deployment of Recurrent Neural Networks and Transformer models. This application is built upon the widely-adopted OpenNMT ecosystem, and is particularly useful for new entrants to the field, as it simplifies the setup of the development environment and creation of train, validation, and test splits. The application offers a graphing feature that illustrates the progress of model training, and employs SentencePiece for creating subword segmentation models. Furthermore, the application provides an intuitive user interface that facilitates hyperparameter customization. Notably, a single-click model development approach has been implemented, and models developed by adaptNMT can be evaluated using a range of metrics. To encourage eco-friendly research, adaptNMT incorporates a green report that flags the power consumption and kgCO${_2}$ emissions generated during model development. The application is freely available.

翻译：adaptNMT是一款开源应用程序，为循环神经网络和Transformer模型的开发与部署提供了简化流程。该应用构建于广泛采用的OpenNMT生态系统之上，尤其适合领域新手使用——它能简化开发环境搭建以及训练集、验证集和测试集的创建流程。该应用具备模型训练进度可视化功能，采用SentencePiece工具构建子词分割模型，并提供直观的用户界面便于超参数定制。特别值得关注的是，其实现了单次点击模型开发方案，且可通过多种评估指标对由adaptNMT开发的模型进行性能评估。为倡导绿色科研，adaptNMT内置了碳排放报告功能，可实时记录模型开发过程中的功耗及千克二氧化碳排放量。该应用完全免费开放。