HumanoidTTT — Consolidation Policy

Initial Double-DQN consolidation weights for HumaniodTTT: Test-Time Capability Reuse for Efficient Humanoid Control.

Model

The policy scores retention actions for a finite-capacity capability store. Each action has a 71-dimensional consolidation feature and is scored by a shared 71 → 128 → 64 → 1 ReLU network with 17,537 parameters. When the ten-slot store is full, the actions are SKIP or REPLACE(j). Online Double-DQN updates use the fraction of subsequent requests with successful reuse between consecutive full-store qualified-miss decisions.

Release files

File	Contents
consolidation_policy.pt	Initial FP32 PyTorch scorer state dictionary, seed 83001.
config.json	Architecture, feature layout, action mapping, online settings, and weight checksum.
SHA256SUMS	File checksums.

This checkpoint is the starting point before online adaptation. It does not contain a prefilled capability store or optimizer/replay state.

Usage

Install the code and download dependencies:

git clone https://github.com/AIGeeksGroup/HumaniodTTT.git
cd HumaniodTTT
pip install -e .
pip install huggingface_hub

import torch
from huggingface_hub import hf_hub_download
from humanoid_ttt import ConsolidationPolicy

path = hf_hub_download("AIGeeksGroup/HumanoidTTT", "consolidation_policy.pt")
weights = torch.load(path, map_location="cpu", weights_only=True)
policy = ConsolidationPolicy(weights, capacity=10, online_learning_rate=3e-5, gamma=0.95)

See the GitHub README for entry applicability, execution feedback, and update interfaces. Pin the model revision and code commit when reproducing experiments.

Dependencies and scope

The 45-dimensional A2 entry-applicability module uses state features and geometric certificates; it has no separate neural-network checkpoint. Applications supply motion-specific certificates, qualification evidence, and the execution runtime. Download frozen generation and tracking models from OMG and HoloMotion.

The released scorer weights alone do not constitute an end-to-end robot controller. Successful loading verifies network compatibility, not complete experimental reproduction.