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wjstx/pick_tube_05_tactile_decoder_deploy
pick_tube_05_tactile_decoder_deploy is a robotics model from wjstx. 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 pytorch.
Private deployment payload for the VB3 direct tactile action decoder ablation.
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Updated Aug 16, 2026
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From the Hugging Face model README
Private deployment payload for the VB3 direct tactile action decoder ablation.
The runtime composes:
lerobot/smolvla_base at revision
c83c3163b8ca9b7e67c509fffd9121e66cb96205;KaiyueChen/pick_tube_01 PEFT adapter at revision
c2bb4296cf7405ac3c0ad89e6f577fa620a660a6;action_tactile direct Transformer decoder.The decoder predicts a physical-unit action chunk shaped [1, 20, 20] after
the saved action postprocessor. Four current-frame tactile RGB images are
required in this exact order:
observation.images.tactile_left_0observation.images.tactile_right_0observation.images.tactile_left_1observation.images.tactile_right_1smolvla_base/: base config and full weights.smolvla_adapter/: PEFT adapter and saved pre/postprocessors.tactile_encoder/: converted encoder weight and parity manifest.decoder/best.pt: formal action+tactile checkpoint selected at epoch 3.tokenizer/: pinned SmolVLM2 tokenizer/processor assets.deployment_manifest.json: revisions, tensor contract, and key hashes.docs/NETWORK_STRUCTURE.md: complete architecture and evaluation protocol.Training data, formal feature cache, optimizer state, smoke checkpoint, and action-only checkpoint are intentionally excluded.
This payload contains the required weights, but the VB3 real-robot client must
use the tactile decoder deployment integration on the ablation branch. The
offline evaluation does not establish real-robot safety or success.
hf download wjstx/pick_tube_05_tactile_decoder_deploy \
--local-dir /home/ljl/assets/pick_tube_05_tactile_decoder_deploy