Document Metatron v1 browser exports and model license
Browse files- LICENSE.pdf +0 -0
- NOTICE.txt +13 -0
- README.md +121 -0
LICENSE.pdf
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NOTICE.txt
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Licensed by NVIDIA Corporation under the NVIDIA Open Model License.
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Copyright (c) 2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
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This notice covers the Metatron G1 ONNX exports in demo/model.onnx and
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racer/network.onnx. See LICENSE.pdf for the complete agreement.
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The two artifacts contain the same learned policy in different runtime graph
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layouts. They are not the separate SAMP scene-interaction policy.
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Robot assets, motion datasets, reference clips and third-party runtime software
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are not included here. Their respective licenses and permissions remain
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separate from the model license. This repository grants no rights to those
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separate assets, including standalone redistribution of demo-only motion clips.
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README.md
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---
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license: other
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license_name: nvidia-open-model-license
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license_link: https://huggingface.co/nvidia/metatron-browser/blob/main/LICENSE.pdf
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language:
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- en
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library_name: onnx
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tags:
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- robotics
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- reinforcement-learning
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- humanoid
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- onnx
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- metatron
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---
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# Metatron v1 — G1 Browser Exports
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## Overview
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ONNX inference exports of the Metatron G1 walking/recovery policy used by the
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Metatron browser demo and G1 Racer. Both files use the same learned policy
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weights, with different runtime interfaces. They are **not interchangeable**.
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This repository does not include the separate SAMP scene-interaction policy.
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| Field | Value |
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| --- | --- |
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| Robot | Unitree G1, 29 controlled joints |
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| Model | Conditional generative control policy with a gated recovery adapter |
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| Inference | Deterministic learned prior; FP32 |
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| Format | ONNX |
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| Integration | ONNX Runtime Web with WebGPU or WebAssembly |
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## Intended Use
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Interactive humanoid control, locomotion and recovery evaluation with the
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matching browser applications. The applications provide physics, observations,
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task goals and control logic; the ONNX files alone are not complete demos.
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Metatron supports deployment workflows beyond the browser, including other
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simulators and real G1 robots. These particular browser exports require their
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matching observation and control interfaces: compatibility is not a safety
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certification or a claim that these exact files have been validated on hardware.
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## Artifacts
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| File | Interface | Size |
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| --- | --- | --- |
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| `demo/model.onnx` | Single-robot pipeline, including observation processing and action conversion | 397,088,354 bytes |
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| `racer/network.onnx` | Six-robot batched network; requires G1 Racer's separate observation processing | 396,370,481 bytes |
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The Racer export changes graph organization and batching, not learned weights.
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Neither artifact is a resumable training checkpoint. Runtime code, robot assets,
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motion clips and application configuration are distributed separately.
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## Inputs and Outputs
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The demo pipeline consumes current G1 state, eight historical state samples,
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raw-action history, ground height, masked future pose/style/velocity goals and
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an explicit `recovery_enabled` input. It returns joint PD targets (`action`),
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PD gains (`stiffness`, `damping`) and `raw_action` for history feedback.
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Recovery targets and the recovery gate remain runtime inputs, not baked goals.
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G1 Racer computes observations outside the neural graph and evaluates all six
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robots in one batch. Its network exposes `action` and `raw_action`; controller
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parameters come from the paired runtime. Do not feed raw demo inputs directly
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to this network or change its batch size without rebuilding and validating it.
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Preserve the paired application's joint/body ordering, quaternion convention,
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history ordering, normalization, target masks, control rate and action mapping.
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Use the matching runtime manifest and ONNX tensor signatures for exact layouts.
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## Runtime Support and Validation
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The browser integrations use MuJoCo WASM for simulation and ONNX Runtime Web for
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inference. WebGPU is recommended on capable devices; CPU/WASM is a fallback and
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does not guarantee real-time six-robot operation. GPU drivers, browsers and
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hardware affect startup time and throughput.
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The demo export's recorded native-to-ONNX checks have maximum absolute errors
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below 3.1e-6 across the checked outputs with recovery enabled and disabled.
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These are numerical export checks, not task-success or real-robot benchmarks.
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Racer's paired application also runs action-parity fixtures at startup.
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For reproducibility, pin downloads to a repository commit rather than `main`.
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Public browser delivery requires anonymous access to the files; never embed a
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Hugging Face access token in client-side code.
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## Limitations and Safety
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- Recovery, balance and tracking can fail, especially outside the evaluated
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states, terrain and command distribution.
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- Game launch assists, low-gravity zones and respawns are application mechanics,
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not capabilities guaranteed by the learned policy or physical robot.
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- The model is not a collision-avoidance system or a safety controller.
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- Hardware use requires independent validation, appropriate joint/torque limits,
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supervised testing, and an emergency-stop mechanism.
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- These exports are not a complete training-reproduction package. No training
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dataset or training checkpoint is included.
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## License and Asset Rights
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Model terms: [NVIDIA Open Model License Agreement](LICENSE.pdf), with the
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required attribution in [NOTICE.txt](NOTICE.txt). The complete agreement
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governs; this card does not replace or extend it.
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Model licensing does not grant rights to motion datasets, recovery reference
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clips, robot meshes, game assets or third-party runtime software. None of those
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assets is included in this model repository. Obtain them through their
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respective distributions and follow their separate terms. Permission to include
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a clip inside a demo or game does not imply permission to redistribute that
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clip as a standalone dataset.
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This repository is currently a private integration preview. Adding these
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documents does not establish public-release clearance or change the release
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status of the associated applications and assets.
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## References
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- [ProtoMotions](https://github.com/NVlabs/ProtoMotions)
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- [ProtoMotions documentation](https://protomotions.github.io/)
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- [NVIDIA Open Model License](https://www.nvidia.com/en-us/agreements/enterprise-software/nvidia-open-model-license/)
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