Instructions to use Spa-Bench/spa-bench-model-molmoact2-step-076596 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- LeRobot
How to use Spa-Bench/spa-bench-model-molmoact2-step-076596 with LeRobot:
- Notebooks
- Google Colab
- Kaggle
MolmoAct2 — Spa-Bench Step 76,596
This checkpoint is released as an anonymous supplementary artifact for a paper under double-blind review. It was evaluated on a physical SO-101 robot in Spa-Bench.
Model details
| Field | Value |
|---|---|
| Checkpoint | End of epoch 12; step 76,596 |
| Inputs | Middle RGB, wrist RGB, six joint positions, and a text instruction |
| Outputs | Six absolute joint-position targets |
| Action horizon | 30 |
| Adaptation | VLM and continuous-action expert updated; token embeddings frozen |
| Optimizer | AdamW; zero weight decay; component-specific learning rates |
Training-data documentation: spa-bench-training-teleoperation-1200.
Physical evaluation
87/120 familiar trials, 156/300 withheld-composition trials, 73/120 matched withheld trials, and 107/120 matched direct-manipulation controls. These are physical rollout results, not simulation metrics.
Rollouts: spa-bench-eval-rollouts-molmoact2-full.
Limitations and safety
Results apply to this checkpoint, SO-101 embodiment, workspace, cameras, objects, and physical protocol. Robot policies can move hardware unexpectedly. Use conservative limits, an accessible emergency stop, a clear workspace, and direct supervision. Do not deploy unattended or in safety-critical settings.
Double-blind release note
Author, institution, source-repository, and archival citation details are intentionally omitted during review. They will be restored in the archival release.
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Model tree for Spa-Bench/spa-bench-model-molmoact2-step-076596
Base model
allenai/MolmoAct2