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

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.

Subscribe:

Do you have technical AWS questions?

ABOUT AWS
Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform, offering over 200 fully featured services from data centers globally. Millions of customers — including the fastest-growing startups, largest enterprises, and leading government agencies — are using AWS to lower costs, become more agile, and innovate faster.

#AWS #AmazonWebServices #CloudComputing