Robotics
PyTorch
Cosmos
xperience10m_task_baseline_suite
embodied-ai
multimodal
xperience-10m
baseline
evaluation
qwen3-omni
Instructions to use cy0307/ropedia-xperience-10m-task-baselines with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Cosmos
How to use cy0307/ropedia-xperience-10m-task-baselines with Cosmos:
# No code snippets available yet for this library. # To use this model, check the repository files and the library's documentation. # Want to help? PRs adding snippets are welcome at: # https://github.com/huggingface/huggingface.js
- Notebooks
- Google Colab
- Kaggle
ropedia-xperience-10m-task-baselines / results /omni_exploration /qwen3_adapter_smoke /RUN_REPORT.md
Qwen3-Omni Adapter Smoke Test
- Base model target:
Qwen/Qwen3-Omni-30B-A3B-Thinking - Qwen3-Omni weights loaded:
false - Episodes:
1 - Windows:
59total,41train,18test - Split:
single_episode_chronological - Feature dimension:
4262 - Adapter soft-token blocks:
11 - Accuracy:
0.0000 - Macro-F1:
0.0000
Why this is the minimum real test
This run uses real Ropedia annotation/video-derived feature blocks. It tests the sensor-adapter side that depth, pose, mocap, contacts, and IMU need before those tokens are attached to Qwen3-Omni. It deliberately avoids downloading the 30B Qwen3-Omni weights until the data path, labels, splits, and storage plan are confirmed.