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act-sotac-tac-mlp
Jingyi-Z/act-sotac-tac-mlp
act-sotac-tac-mlp is a machine learning model from Jingyi-Z. Use it for the machine learning 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.
ACT policy with one added transformer encoder token from a tactile encoder. Variant: MLP encoder on the current tactile frame (312 values), trained end to end.
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At a glance
- Library
- lerobot
- License
- apache-2.0
- Access
- Public
- Created
- Sep 16, 2026
- Updated
- Sep 16, 2026
- SHA
- e1d8a0dc
Model card
From the Hugging Face model README
act-sotac-tac-mlp
ACT policy with one added transformer encoder token from a tactile encoder. Variant: MLP encoder on the current tactile frame (312 values), trained end to end.
Trained on episodes 0 to 70 of Jingyi-Z/sotac (red foam ball into container, SO-101, top and wrist cameras, Paxini fingertip forces at 30 Hz), 100k steps, batch 8, stock ACT hyperparameters, lerobot 0.4.4 with a tactile-encoder patch. The config carries tactile_key, tactile_hidden and related fields: apply the matching ACT patch before loading, or strip those keys for stock lerobot. Companion variants: act-sotac-tac-{mlp,pred,esn,esnpred}. Baseline without tactile: act-sotac-runA.
- Library
- lerobot
- License
- apache-2.0
- Created
- Sep 16, 2026
- Updated
- Sep 16, 2026