Instructions to use Sa74ll/LocalModels-ACT-bimanual with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- LeRobot
How to use Sa74ll/LocalModels-ACT-bimanual with LeRobot:
# 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
LocalModels / ACT-bimanual
Entry ACT-bimanual by team LocalModels (Saleh Alsharideh, Independent) to the CoRL 2026 RoboEval Diagnostic Bimanual Challenge. Official score 0.9861, 399 of 400 episodes successful.
Seven tasks run hand-designed RGB-D controllers (no learned weights); LiftPot runs an Action Chunking Transformer (ACT) trained on the demonstrations and fine-tuned in simulation with GRPO. Code, report and explainer videos: github.com/Sa74ll/RoboevalChallenge.
| Path | Content |
|---|---|
submission/ |
the submitted bundle: metadata.yaml, policy/, checkpoint/ (seven hybrid.json controller selectors and the LiftPot ACT weights) |
official_run/ |
the official run (seeds 1000-1049): results.json and the 400 episode logs |
SHA1SUMS.txt |
SHA-1 of every file in submission/ |
The submission archive was packaged without checkpoint/; its checkpoint_url points to submission/checkpoint here.
Run
Needs RoboEval at tag corl2026-challenge.
hf download Sa74ll/LocalModels-ACT-bimanual --include "submission/*" --include SHA1SUMS.txt --local-dir ACT-bimanual
cd ACT-bimanual && sha1sum -c SHA1SUMS.txt
pip install -r submission/policy/requirements.txt
python -m roboeval.challenge.evaluate --submission submission --workers W --gpus 0
Results (official run)
| Task | Policy | Successes | Score |
|---|---|---|---|
| CubeHandover | controller | 50 | 1.000 |
| LiftPot | ACT | 50 | 0.999 |
| LiftTray | controller | 50 | 1.000 |
| PackBox | controller | 49 | 0.954 |
| PickSingleBookFromTable | controller | 50 | 0.987 |
| RotateValve | controller | 50 | 1.000 |
| StackSingleBookShelf | controller | 50 | 1.000 |
| StackTwoBlocks | controller | 50 | 0.948 |
| Suite | 399 / 400 | 0.9861 |
Training data and every use of simulator state: the report, Sec. 3. The files here equal the submitted ones except
three edits that do not change behaviour (no contact e-mail in metadata.yaml, local paths shortened in the LiftPot
configs, a license notice in modeling_act.py); see GitHub.
License
Apache-2.0. modeling_act.py is modified from LeRobot (Apache-2.0).