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pravsels/
molmoact2_fold_tea_towel_quantile_norm_fix_25k

Name: molmoact2_fold_tea_towel_quantile_norm_fix_25k
Availability: InStock

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molmoact2_fold_tea_towel_quantile_norm_fix_25k

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


Policy	MolmoAct2 (`policy.type=molmoact2`)
Init checkpoint	allenai/MolmoAct2
Dataset	villekuosmanen/armnetbench_fold_tea_towel
Task	`fold_tea_towel`
Action dim	12 (bimanual)
Cameras	`top`, `left_wrist`, `right_wrist`
Training	25k steps, QUANTILES norm, freeze, batch 32 global, Isambard GH200
Prior HF repo	pravsels/molmoact2_fold_tea_towel
W&B project	molmoact2_fold_tea_towel_quantile_norm_fix_25k
W&B run	8daw5l83

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 e214656548e42bd69dc644d6fcca71d7c1a2a79453e24c155b0d7471948d9531 | | policy_preprocessor.json | 2,523 bytes, sha256 aac2ee4e61c26a5322c9b3e2f727ce060c90071e012185d9f39cceb2d43ea04a | | policy_postprocessor.json | 758 bytes, sha256 8690a8e7015281571c9de7d88073b302cd03123e5f677ea582c669dbf014e7ad | | train_config.json | 8,840 bytes, sha256 d76c1f2451451b9dfad253af77efd4f91bae2c0b0d8fc3d995bc6e6f823d52df |

Verify after download:

bash

sha256sum model.safetensors
# expected: e214656548e42bd69dc644d6fcca71d7c1a2a79453e24c155b0d7471948d9531

Usage

python

from lerobot.policies.molmoact2.modeling_molmoact2 import MolmoAct2Policy
policy = MolmoAct2Policy.from_pretrained("pravsels/molmoact2_fold_tea_towel_quantile_norm_fix_25k")