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vla-jepa-folding
chalkp/vla-jepa-folding
vla-jepa-folding is a robotics model from chalkp. Use it for the robotics task on the model card, and read the license before you ship it in a product. It is set up for lerobot. The card lists the license as apache-2.0.
This model is a VLA-JEPA policy fine-tuned for bimanual shirt folding on the OpenArm robot.
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2.3B
4.9 GB on disk
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.safetensors4.9 GB · 100%
Parameter types
How the weights are stored.
BF162.1B · 93%
Base models
Datasets
Model card
From the Hugging Face model README
VLA-JEPA Fine-tuned with Unfolding Robotics dataset
Model Description
This model is a VLA-JEPA policy fine-tuned for bimanual shirt folding on the OpenArm robot.
- Base model: lerobot/VLA-JEPA-Pretrain (VLA-JEPA pretrained on DROID)
- Fine-tuning dataset: lerobot/high_quality_folding
Training Details
Slurm Scripts and training config for job submission on LANTA are already provided in the repository.
- Cross-embodiment transfer: DROID (7D single-arm) → OpenArm (16D bimanual)
- Re-initialized layers: action_encoder, action_decoder, state_encoder
- Frozen backbone: Qwen3-VL-2B (inference only)
- Trainable params: 155M / 2.3B total
- Optimizer: AdamW, lr=3.75e-5, weight_decay=0.01
- Schedule: Cosine decay with warmup
- Batch size: 128
- Steps: 40000
- Precision: BF16
- RABC: Enabled (kappa=0.0265, SARM progress scores)
- Normalization: QUANTILES for state and action
- Training time: ~48-49 hours on 4x LANTA GPU Node (4xA100 40GB SXM)
Loss Curve
Usage
from lerobot.policies import make_policy
policy = make_policy(pretrained_name_or_path="chalkp/vla-jepa-folding")
- Task
- Robotics
- Library
- lerobot
- License
- apache-2.0
- Created
- Jun 12, 2026
- Updated
- Jun 12, 2026