![]() ![]() The status should transition from Deploying to Deployed.ĭevelopers should use the Category ID when making translation requests with Microsoft Translator Text API V3. Select en-de with sample data and select Publish. Select Publish model from the left navigation menu. For more information, see Translator pricing. You can only publish one model per project however, you can publish a model to one or multiple regions depending on your needs. A project might have one or many successfully trained models. Publishing your model makes it available for use with the Translator API. Human evaluate translation from New model (custom model), and Baseline model (our pre-trained baseline used for customization) against Reference (target translation from the test set).Select Test model from the left navigation menu.Once your training has completed successfully, inspect the test set translated sentences. If you train with our shared customer sample datasets, BLEU score will be different than the image. Select "Global" for Select resource region from the dropdown list. Type Contoso MT models for Workspace name and select Next. Both tokens are needed for authentication and to ensure that you aren't signed out during your live session or while training your models. Use the cloud-based, secure, high performance, highly scalable Microsoft Translator Text API V3 to make translation requests.Īfter your sign-in to Custom Translator, you'll be asked for permission to read your profile from the Microsoft identity platform to request your user access token and refresh token. Your custom model is made available for runtime translation requests. This score indicates the quality of your translation system. ![]() The testing set is used to compute the BLEU score. A 10,000 parallel sentence is the minimum requirement to train a model. It will use a random subset of sentences from your training documents, and exclude these sentences from the training data itself. If only training data is provided when queuing a training, Custom Translator will automatically assemble tuning and testing data. When you train a model, three mutually exclusive document types are required: training, tuning, and testing. ![]() The outcome of a successful training is a model. A model is the system that provides translation for a specific language pair. It doesn't matter which language is marked as "source" and which language is marked as "target"-a parallel document can be used to train a translation system in either direction. One document in the pair contains sentences in the source language and the other document contains sentences translated into the target language. Parallel documents are pairs of documents where one (target) is the translation of the other (source). For example, if you have both an English-to-Spanish project and a Spanish-to-English project, the same documents will be included in both projects. Each project includes all documents that are uploaded into that workspace with the correct language pair. A project is a wrapper for models, documents, and tests. All the work you do in Custom Translator is done inside a specific workspace.Ĭreate a project. A workspace can contain multiple projects, models, and documents. A workspace is a work area for composing and building your custom translation system. You can read an overview of translation and custom translation, learn some tips, and watch a getting started video in the Azure AI technical blog. Once you have the above prerequisites, sign in to the Custom Translator portal to create workspaces, build projects, upload files, train models, and publish your custom solution. Custom Translator portalĬustom Translator does not support creating workspace for a Translator Text API resource created inside an Enabled VNet. You can find these values on the Azure portal Keys and Endpoint page:įor more information, see how to create a Translator resource. You'll paste your key and endpoint into the code below later in the quickstart. You'll need the key and endpoint from the resource to connect your application to the Translator service. Once you have an Azure subscription, create a Translator resource in the Azure portal to get your key and endpoint. To use the Custom Translator portal, you'll need the following resources: In this quickstart, you'll learn to build custom solutions for your applications across all supported languages. Translator powers many Microsoft products and services used by thousands of businesses worldwide to perform language translation and other language-related operations. Translator is a cloud-based neural machine translation service that is part of the Azure Cognitive Services family of REST API that can be used with any operating system. ![]()
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