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Record, train, and deploy from one place with Strands Agents, LeRobot, and Hugging Face Storage Buckets

Updated September 26, 2026 · 2:44 PM · source date August 13, 2026

Summary

Record, train, and deploy from one place with Strands Agents, LeRobot, and Hugging Face Storage Buckets Record, train, and deploy from one place with Strands Agents, LeRobot, and Hugging Face Storage Buckets Enterprise Article Published August 13, 2026 Upvote 34 Sundar Raghavan rsundaraws amazon Steven Palma imstevenpmwork amazon Cagatay Cali cagataydev amazon Arron Bailiss arronbailiss amazon Yin Song yinsong1986 amazon A walkthrough of the streaming data loop in Strands Robots, one agent loop that records robot demonstrations, trains on them by reading straight from the Hub, and deploys the policy back to hardware, with the dataset in the same on-disk LeRobot format the whole way through. You have an agent that can already record a demonstration and push it to the Hugging Face Hub .

Why it matters

This OpenSourceRelease is relevant to the technology intelligence record because it involves Hugging Face, Amazon Web Services, Amazon, Apple. The source article should remain the factual reference for follow-up coverage.

Key facts
  • Record, train, and deploy from one place with Strands Agents, LeRobot, and Hugging Face Storage Buckets Enterprise Article Published August 13, 2026 Upvote 34 Sundar Raghavan rsundaraws amazon Steven Palma imstevenpmwork amazon Cagatay Cali cagataydev amazon Arron Bailiss arronbailiss amazon Yin Song yinsong1986 amazon A walkthrough of the streaming data loop in Strands Robots, one agent loop that records robot demonstrations, trains on them by reading straight from the Hub, and deploys the policy back to hardware, with the dataset in the same on-disk LeRobot format the whole way through.
  • You have an agent that can already record a demonstration and push it to the Hugging Face Hub .
  • Now you want to run that loop continuously: collect episodes through the day, train a policy on the growing dataset, deploy it, and pull the next batch back to improve it.
  • Run that loop once and every piece works.
  • Run it every day and you start paying for the same byte transfers over and over.
  • The recordings you upload keep growing, each training run copies the whole dataset to the GPUs before it starts, and every new checkpoint ships out while the next batch of recordings comes back.
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