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Document release manifest and download tracking

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  1. README.md +9 -2
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@@ -16,6 +16,8 @@ pipeline_tag: reinforcement-learning
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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>
@@ -145,7 +147,7 @@ variant.
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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 3-point 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
@@ -161,6 +163,11 @@ hardware.
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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
@@ -183,7 +190,7 @@ See the [Download Models guide](https://nvlabs.github.io/GR00T-WholeBodyControl/
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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 3-point teleoperation and SONIC-backed VLA
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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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+ [![Hugging Face downloads](https://img.shields.io/huggingface/dm/nvidia/GEAR-SONIC)](https://huggingface.co/nvidia/GEAR-SONIC)
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+
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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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+
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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