dfreq / upstream-base-card.md
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Publish Sprint declared-start specialist, local 0.848 s
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---
tags:
- microduck
- microduck-policy
- robotics
- onnx
library_name: microduck
pipeline_tag: robotics
base_model: suraj-phanindra/microduck-sprint-hc5-aifund
base_model_relation: finetune
---
# dfreq
A neural-feedback policy for the Microduck Arena **2 m Sprint**, published by **djduecaster**. This is the V45 physical-leg-adapter version of our 0.856-second local result, not a new speed record.
## Local verification
On 25 October 2026, the unchanged artifact was checked with the pinned official Arena CPU evaluator (runner version 4):
- Mean finish time: **0.856 s**, **5/5 finishes**, selected command **1.15 m/s**.
- Individual times: **0.86, 0.86, 0.86, 0.86, 0.84 s**.
- Verification covered the complete official 21-command scan and 12 additional finalist races. A separate five-start replay exactly matched the previously saved observations, actions, race traces and settling traces.
- These five starts were used during optimization. This is an in-sample result, **not a held-out robustness claim**. Most other commanded speeds failed in the scan; this is a specialized sprint policy, not a generally reliable walker.
- **Local timing is not a server leaderboard result.** The Space evaluates the submitted revision independently, and hardware/software differences can change the outcome.
## Controller and provenance
Input: the standard 61-dimensional observation, including actual previous actions; output: 14 joint-position actions, at 50 Hz. Observation normalization is included. Runtime control uses neural feedback and a physical-state leg adapter; it contains no explicit clock counter, seed-ID input, seed-fingerprint selector or trajectory lookup table.
The graph retains the frozen [hc5 base](https://huggingface.co/suraj-phanindra/microduck-sprint-hc5-aifund/tree/c0c2897894cbab30a74a16e58cc93603dcfe581f), adds our trained residual, and adds a small physical-state adapter affecting knee/ankle outputs. The residual's training lineage used sanitized outputs from [game-sprinter-remix4](https://huggingface.co/jrubiosainz/microduck-game-sprinter-remix4/tree/175eba5581c9cbc038588ff1a1f406afc2e3a446). That teacher uses clock/seed-specific mechanisms; **those mechanisms are not present in this deployed graph**. Subsequent residual/adapter optimization used native Arena outcomes on the original five starts.
Credit: **suraj-phanindra** (hc5), **juicenv** and **namenu** (base lineage), **jrubiosainz**, **dashi** and **Muhammadsafi** (teacher lineage), and **Pollen Robotics** (robot, training ecosystem and Arena).
## Artifact and limitations
`policy.onnx`: **1,137,169 bytes**
SHA256: `4aa8b27e4e02fbe9dcea1cae2d07f9505b51a62418dad853d2ff55e6a924a243`
**Simulation only. No physical-robot validation or safety claim.** No training code or external runtime helpers are required to load this ONNX; no claim is made that all training code is published here.
The inspected upstream model repositories do not declare standalone model licenses. This repository does **not** relicense inherited weights as MIT, Apache, or another open-source license. Review the linked upstream terms and [Hugging Face Terms of Service](https://huggingface.co/terms-of-service), including their public-repository provisions, before reuse. A general off-platform redistribution license is not asserted.