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i4h-workflow-train-rl

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Use when training, evaluating, or exporting Workflow policies with online RSL-RL or RLinf, including RL checkpoint and Workflow handoff.

skills/i4h-workflow-train-rl/SKILL.md

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# Train a Workflow Policy with RL

## Purpose

Resolve a maintained online-RL profile, verify its Scene/objective/model contracts, run the selected vectorized trainer, evaluate and export its artifact, and hand that artifact to normal Workflow policy validation.

## Requirements

- Run the Workflow setup skill first so its uv environments and pinned third-party checkouts are available.
- Use a CUDA-capable Isaac Lab/Arena runtime for the RSL-RL workflow.
- For Trocar, provide a local GR00T N1.5 3B base or SFT checkpoint and two visible local GPUs for the isolated controller and simulator runtimes. A compatible checkpoint is a complete local Hugging Face directory that the pinned GR00T N1.5/RLinf loader accepts without conversion; it must retain the N1.5 3B architecture and support the maintained three-camera plus 28-joint observation mapping and 28-D policy action head. Reject another model family, an exported inference-only Task artifact, or a checkpoint whose config changes those interfaces.

## Instructions
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