LibreVLA API

Load

Install libreyolo[vla] on Python 3.12 or later. LibreVLA("smolvla-base") loads the base policy; LibreVLA("act") and LibreVLA("diffusion") construct untrained policies. A checkpoint directory is also accepted.

Predict

model.predict(source, state=..., instruction=...) accepts camera frames, frame dictionaries and streams. cameras= fixes slot ordering. set_instruction() persists a language instruction. Supply the state and camera representations the policy was trained on.

Results.actions provides data, first, names, fps and instruction. Call reset() between episodes, especially for Diffusion Policy's observation history.

Train and validate

train(data=...) accepts a LeRobot v3 directory or Hub dataset ID. It returns checkpoint directory paths, including best. val(data=..., split="val", max_batches=...) measures offline action error. See robot policies for metrics and the policy models for training differences.

There is no action-policy CLI, tracking or export. Checkpoints contain libreyolo_vla.json plus upstream configuration, policy tensors and processors.