Customizing foundation models on Amazon SageMaker | Step 4: Prepare datasets for fine-tuning

Опубликовано 24 июля 2024, 15:36

In this video, you will learn how to label the data using Amazon SageMaker Ground Truth. You can collect human labeled data through automated workflow or an AWS managed workforce. For example, you can get data like Q&A pairs, image/video captions, or preference ranking of responses. And then you can upload the custom, labeled datasets to Amazon S3, analyze data using SageMaker notebooks, and convert datasets into tokens.

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