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pravsels/
molmoact2_eyedrops_shelf_quantile_norm_fix_25k

Name: molmoact2_eyedrops_shelf_quantile_norm_fix_25k
Availability: InStock

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molmoact2_eyedrops_shelf_quantile_norm_fix_25k

Fine-tuned MolmoAct2 (action-expert-only) for eyedrops_shelf on SO101 data.


Policy	MolmoAct2 (`policy.type=molmoact2`)
Init checkpoint	allenai/MolmoAct2
Dataset	pravsels/object_top_shelf_remote
Task	`eyedrops_shelf`
Action dim	6 (single-arm)
Cameras	`top`, `wrist`, `front`
Training	25k steps, QUANTILES norm, freeze, batch 32 global, Isambard GH200
Prior HF repo	pravsels/molmoact2_eyedrops_shelf
W&B project	molmoact2_eyedrops_shelf_quantile_norm_fix_25k
W&B run	rqvsh5n5

Checkpoints

The checkpoint (local step 025000, 25k training steps) lives at the repository root for direct loading.

Verification

| Checkpoint step | 025000 | | Source path | checkpoints/025000/pretrained_model/ | | model.safetensors | 10,884,573,720 bytes, sha256 ea05537186ec6afaf66e1047de4e363be964f7ccf9cc94affabb13dc2485ede0 | | policy_preprocessor.json | 2,495 bytes, sha256 e7c8b8293cb0265a01f83278033272efcb21b4c7bfb031cfbd683ed74ee7b139 | | policy_postprocessor.json | 757 bytes, sha256 6dbed1e1ec69e8c50f3a04c1f144a54231e3ef508f15fd7896ead43ea645b033 | | train_config.json | 8,260 bytes, sha256 6acc38482b2308fc9997f34cf67f70d75da36d2609b6084de53551d77c3ee833 |

Verify after download:

bash

sha256sum model.safetensors
# expected: ea05537186ec6afaf66e1047de4e363be964f7ccf9cc94affabb13dc2485ede0

Usage

python

from lerobot.policies.molmoact2.modeling_molmoact2 import MolmoAct2Policy
policy = MolmoAct2Policy.from_pretrained("pravsels/molmoact2_eyedrops_shelf_quantile_norm_fix_25k")