What you need
- Isaac 0.5 enabled for your organization. Email team@dreamscalelabs.com to request it.
- A Hugging Face repo with your Isaac 0.5 fine-tune, exported in full, with the normalization statistics from its training data.
- A Hugging Face read token if the repo is private.
1. Create the deployment
- Dashboard
- CLI
- Open Deployments and choose Create deployment.
- Enter the repo as
owner/name, add a read token if it is private, and choose Detect. - Check the Robot fields. SO-101 and Bimanual YAM presets fill them for you; Custom takes your own cameras, image size, and widths.
- Check Robot unit conversion (see below) and pick the region nearest your robot.
- Choose Create deployment.
The deployment shows Ready and an ID like
ckpt_....Robot unit conversion
The conversion turns the model’s outputs into your robot’s joint angles, using your checkpoint’s normalization statistics. Each training dataset has its own statistics. Choose the one recorded on this robot, or the robot moves to the wrong positions. Dreamscale selects it for you when the repo names it or only one fits.2. Run it
On a supported robot, finish its setup first (SO-101 or Bimanual YAM), then:observation with dreamscale.robot.observe.
3. Keep it warm (optional)
A cold start takes 2–3 minutes. Keep-warm keeps the GPU up after the last robot disconnects, so the next robot connects in seconds.- One robot at a time uses the warm GPU. A second robot gets its own cold start.
- Each GPU runs at most 24 hours. A session still connected then ends cleanly, so reconnect in long-running code. With Always, a replacement is ready.
- To move Always to a new deployment without a gap, run
dreamscale deployments keep-warm ckpt_new always --take-over-from ckpt_old.