Hosting Open-Source Translation Models on AWS SageMaker for Automated Blog Localization
In this post, we’ll take a deep dive into deploying an open-source text-to-text translation (T2TT) model on AWS SageMaker and integrate it into a Nuxt Content blog. We’ll automate the workflow through a CI pipeline powered by GitHub Actions, enabling our blog to be read in nearly 100 languages.
SageMaker is AWS's managed platform that simplifies building, training, and deploying machine learning models for developers and data scientists.
We'll need to setup a bit of permissions for AWS before we dive in. Let's create an AWS IAM role for our SageMaker application, following these steps:
Performance comparison between Facebooks main T2TT models. A future project may want to use both models, utilizing the benefits of both via dynamic mapping of the model to the particular language translation direction.
ChrF++ (Character n-gram F-score) is a metric used to evaluate machine translation quality that builds upon the original ChrF metric.
