Abstract
adaptNMT streamlines all processes involved in the development and deployment of RNN and Transformer neural translation models. As an open-source application, it is designed for both technical and non-technical users who work in the field of machine translation. Built upon the widely-adopted OpenNMT ecosystem, the application is particularly useful for new entrants to the field since the setup of the development environment and creation of train, validation and test splits is greatly simplified. Graphing, embedded within the application, illustrates the progress of model training, and SentencePiece is used for creating subword segmentation models. Hyperparameter customization is facilitated through an intuitive user interface, and a single-click model development approach has been implemented. Models developed by adaptNMT can be evaluated using a range of metrics, and deployed as a translation service within the application. To support eco-friendly research in the NLP space, a green report also flags the power consumption and kgCO$_{2}$ emissions generated during model development. The application is freely available.
Abstract (translated)
adaptNMT 简化了涉及机器翻译开发和部署的所有过程。 作为一款开源应用程序，它旨在为该领域内的技术用户和非技术用户提供便利。 基于广泛采用的 OpenNMT 生态系统，该应用程序特别对新进入领域的人有所帮助，因为开发环境和工作流程的设置大大简化了。 图形化嵌入应用程序中，展示了模型训练的进展，而 SentencePiece 则用于创建分词模型。 通过直观的用户界面，促进了超参数的自定义，并实现了一种单击式模型开发方法。 由 adaptNMT 开发的数据模型可以使用一系列指标进行评估，并部署为应用程序内的翻译服务。 为支持 NLP 空间内的环保研究，该应用程序还免费提供了一份绿色报告，报告了模型开发过程中产生的功耗和 kgCO$_{2}$ 排放量。 该应用程序是免费的。
URL
https://arxiv.org/abs/2403.02367
