Record, train, and deploy from one place with Strands Agents, LeRobot, and Hugging Face Storage Buckets
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Hugging Face and AWS Strands Robots enable a loop where robots can record demonstrations, train on growing datasets, and deploy new models without repeatedly downloading the same data.
Using Hugging Face Storage Buckets (a storage system that syncs only changed parts) and streaming from Hub keeps the process efficient day after day. A blog post shows how to build this in practice: a robot records data via LeRobot format, syncs data to a bucket, training streams the dataset directly from Hub without downloading everything locally, and a trained model deploys back to the robot with a simple code change.
Run that loop once and every piece works. Run it every day and you start paying for the same byte transfers over and over.
Vibekollen prepared this summary with AI from the original publication. The content belongs to Hugging Face.
