# transfer()

Measure what a policy loses moving to a new embodiment — source and target rates with intervals, and the clusters that opened.

Policies are trained on one body and deployed on another, and the distance
between those two numbers is where deployments die. `roborama.transfer()`
measures it: the same policy on the same task, on the embodiment it was
trained on and the embodiment you intend to ship — both with n and intervals,
plus the failure clusters that exist only on the new body.

## The call

*Example: roborama.transfer()*

**Python**

```python
import roborama  # reads ROBORAMA_API_KEY from the environment

policy = roborama.Policy.checkpoint(hf="acme/skill-v4", runtime="openpi")

gap = roborama.transfer(
    policy=policy,
    source="aloha-bimanual@fw3.1",   # the embodiment it was trained on
    target="g1-edu-pro@fw2.3",
    task="fold_towel@v2",
)

print(gap.report())
# source: n=380  rate=0.942  ci95=(0.914, 0.961)
# target: n=340  rate=0.715  ci95=(0.665, 0.760)
# failure clusters opened in transfer: [grasp_slip, wrist_singularity]
```

**TypeScript**

```typescript
import Roborama from "@roborama/sdk"; // reads ROBORAMA_API_KEY

const roborama = new Roborama();

const gap = await roborama.runs.create({
  kind: "transfer",
  policy: { type: "checkpoint", hf: "acme/skill-v4", runtime: "openpi" },
  source: "aloha-bimanual@fw3.1", // the embodiment it was trained on
  target: "g1-edu-pro@fw2.3",
  task: "fold_towel@v2",
});

const report = await gap.report();
console.log(report);
// source: n=380  rate=0.942  ci95=(0.914, 0.961)
// target: n=340  rate=0.715  ci95=(0.665, 0.760)
```

**cURL**

```bash
curl https://api.roborama.com/v1/runs \
  -H "Authorization: Bearer $ROBORAMA_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "kind": "transfer",
    "policy": { "type": "checkpoint", "hf": "acme/skill-v4",
                "runtime": "openpi" },
    "source": "aloha-bimanual@fw3.1",
    "target": "g1-edu-pro@fw2.3",
    "task": "fold_towel@v2"
  }'
```

**Agent (tool-use payload)**

```json
{
  "type": "tool_use",
  "name": "roborama_transfer",
  "input": {
    "policy": { "type": "checkpoint", "hf": "acme/skill-v4",
                "runtime": "openpi" },
    "source": "aloha-bimanual@fw3.1",
    "target": "g1-edu-pro@fw2.3",
    "task": "fold_towel@v2"
  }
}
```

## Reading the gap

The canonical `fold_towel@v2` gap: on the source, `aloha-bimanual@fw3.1` — the
rig the policy was trained on — the rate is 0.942 (n=380, ci95 0.914–0.961).
On the target, `g1-edu-pro@fw2.3`, it is 0.715 (n=340, ci95 0.665–0.760). The
intervals are nowhere near overlapping: a 22.7-point drop that no amount of
sampling luck explains. That is the real number to plan a deployment around —
not the source rate that made the demo look ready.

## What opened in transfer

The gap report does more than subtract two rates. It names the failure
clusters that were absent or negligible on the source and material on the
target — here, `grasp_slip` and `wrist_singularity` — which turns "the policy
got worse" into a work list. The target's dex3-1 hands present different
contact geometry than the source's grippers, and `grasp_slip` is that
difference biting; `wrist_singularity` is the target's arm kinematics hitting
configurations the source arms never encountered on the same trajectories.
Each cluster links to its episodes, so the diagnosis comes with video, MCAP
telemetry, and commanded-versus-executed traces rather than a hunch.

## Closing the gap

The episodes are also the remedy. Target-embodiment failures export in
training-ready formats — `run.export(format="lerobot")`, or `"rlds"` — subject
to your own data posture, since `train_on_failures` guards *our* use of them,
not yours. Fine-tune on target-embodiment data, re-run `transfer()`, and
watch the two intervals converge; when they are close enough to argue about,
graduate to [matrix()](/docs/primitives/matrix/) and put the new embodiment
in the release grid.

The full workflow — measure, fine-tune, re-measure, and when to stop — is the
[transfer gap guide](/docs/guides/transfer-gap/).

## Where next

- [Transfer gap guide](/docs/guides/transfer-gap/) — the end-to-end workflow.
- [compare()](/docs/primitives/compare/) — paired A/B when both candidates run on one embodiment.
- [Data contract](/docs/concepts/data-contract/) — export formats and ownership.