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A deployment serves your own fine-tune from Hugging Face, shaped to your robot.

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What you need

  • Isaac 0.5 enabled for your organization. Email team@dreamscalelabs.com to request it.
  • A Hugging Face repo with your full Isaac 0.5 fine-tune and the normalization statistics from its training data. For a private repo, set HF_TOKEN.

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1. Create it

Use --preset bimanual_yam for a bimanual YAM. The first build takes about 15 minutes. dreamscale deployments list then shows it as Ready with an ID like ckpt_.... You can also create one on the Deployments page.

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2. Run it

After the robot’s setup (SO-101 or Bimanual YAM):
From Python:
Build observations with dreamscale.robot.observe, using the camera keys and state width shown on the deployment’s page.

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3. Keep it warm (optional)

A cold start takes 2–3 minutes. Keep-warm keeps a GPU ready between runs, and is billed like connected time: