Document release manifest and download tracking
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README.md
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# GEAR-SONIC: Supersizing Motion Tracking for Natural Humanoid Whole-Body Control
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<div align="center">
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<img src="sonic-preview-gif-480P.gif" width="800">
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</div>
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| **Default SONIC (original release)** | Top-level deployment files; PyTorch checkpoint under `sonic_release/` | 10 frames at 20 ms spacing, approximately 200 ms | General-purpose motion tracking, planning, and teleoperation. G1 and teleoperation references use `step5`. |
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| **Low-latency teleoperation** | `low_latency/` | 4 frames at 20 ms spacing, approximately 80 ms | Reduced-reference-lookahead controller for responsive teleoperation and VLA execution. G1 and teleoperation references use `step1`. |
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| **SONIC v1.1** | `sonic_v1_1/` | 10 frames at 20 ms spacing, approximately 200 ms | Robot-heading-normalized controller trained with wrist-pose augmentation for heading-stable
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All variants use 64-dimensional universal motion tokens and a 29-DoF action
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decoder. Inference is powered by TensorRT and runs on both desktop and Jetson
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| SONIC v1.1 policy | `sonic_v1_1/model_encoder.onnx`, `sonic_v1_1/model_decoder.onnx`, `sonic_v1_1/observation_config.yaml` | Robot-heading-normalized G1 controller variant |
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| SONIC v1.1 PyTorch checkpoint | `sonic_v1_1/last.pt` | Training checkpoint and configs for SONIC v1.1 |
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**Quick download** (requires `pip install huggingface_hub`):
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```python
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The `sonic_v1_1/` variant uses robot-heading-normalized target orientation
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and a 10-frame SMPL/wrist reference horizon. It was trained with wrist-pose
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augmentation and is intended for
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policies trained against this controller.
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```bash
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# GEAR-SONIC: Supersizing Motion Tracking for Natural Humanoid Whole-Body Control
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[](https://huggingface.co/nvidia/GEAR-SONIC)
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<div align="center">
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<img src="sonic-preview-gif-480P.gif" width="800">
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</div>
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|---|---|---|---|
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| **Default SONIC (original release)** | Top-level deployment files; PyTorch checkpoint under `sonic_release/` | 10 frames at 20 ms spacing, approximately 200 ms | General-purpose motion tracking, planning, and teleoperation. G1 and teleoperation references use `step5`. |
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| **Low-latency teleoperation** | `low_latency/` | 4 frames at 20 ms spacing, approximately 80 ms | Reduced-reference-lookahead controller for responsive teleoperation and VLA execution. G1 and teleoperation references use `step1`. |
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| **SONIC v1.1** | `sonic_v1_1/` | 10 frames at 20 ms spacing, approximately 200 ms | Robot-heading-normalized controller trained with wrist-pose augmentation for heading-stable whole-body teleoperation and SONIC-backed VLA policies. G1 and teleoperation references use `step5`; this is not the low-latency model. |
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All variants use 64-dimensional universal motion tokens and a 29-DoF action
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decoder. Inference is powered by TensorRT and runs on both desktop and Jetson
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| SONIC v1.1 policy | `sonic_v1_1/model_encoder.onnx`, `sonic_v1_1/model_decoder.onnx`, `sonic_v1_1/observation_config.yaml` | Robot-heading-normalized G1 controller variant |
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| SONIC v1.1 PyTorch checkpoint | `sonic_v1_1/last.pt` | Training checkpoint and configs for SONIC v1.1 |
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The root [`config.json`](https://huggingface.co/nvidia/GEAR-SONIC/blob/main/config.json)
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is the canonical release manifest for all variants and shared artifacts. Include
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it when downloading selected files directly; Hugging Face uses this query file
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for repository-level download statistics.
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**Quick download** (requires `pip install huggingface_hub`):
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```python
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The `sonic_v1_1/` variant uses robot-heading-normalized target orientation
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and a 10-frame SMPL/wrist reference horizon. It was trained with wrist-pose
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augmentation and is intended for whole-body teleoperation and SONIC-backed VLA
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policies trained against this controller.
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```bash
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