Instructions to use rslxcvg/molmoact2-banana-frombase-prod-r128-c010-rw3-w8-20260519 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- LeRobot
How to use rslxcvg/molmoact2-banana-frombase-prod-r128-c010-rw3-w8-20260519 with LeRobot:
- Notebooks
- Google Colab
- Kaggle
MolmoAct2 Banana Diagnostic - frombase prod r128 c010 rw3 w8
Diagnostic MolmoAct2 checkpoint for SO-101 banana color-conditioned pick-and-place.
Important: this checkpoint is for directionality/robot diagnostic testing only. It did not pass the strict offline robot-ready gates from the overnight evaluation.
Source
- Run:
molmoact2_overnight_frombase_prod_r128_c010_rw3_w8_gpu5_20260519_fullcoverage_v1 - Checkpoint step:
010000 - Dataset:
rslxcvg/banana_act_direct_color_simple_v1_molmo_compat - Base checkpoint:
allenai/MolmoAct2-SO100_101 - Norm tag:
so100_so101_molmoact2 - Gripper normalization: enabled
Offline Metrics
| metric | value |
|---|---|
| mixed rank | 1 |
| low_t accuracy | 0.889 |
| pan_rank | 1.000 |
| pan5 degrees | 18.937 |
| final_pan degrees | 61.162 |
| outside stats pct | 0.000 |
| horizon gripper MAE | 1.205 |
Strict gates were low_t >= 0.95, pan_rank == 1.0, pan5 >= 20, outside == 0, and h_grip <= 2.5. This checkpoint failed the low_t and pan5 gates.
Files
The repository root is the LeRobot/MolmoAct2 pretrained_model directory and should be usable as a policy checkpoint path after snapshot_download.
Evaluation artifacts are under eval/.
- Downloads last month
- 4