Add robotics pipeline tag and remove arxiv tag from metadata

#1
by nielsr HF Staff - opened
Files changed (1) hide show
  1. README.md +4 -4
README.md CHANGED
@@ -1,13 +1,13 @@
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  ---
 
 
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  language:
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  - en
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  tags:
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  - robotics
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  - humanoidtoolbench
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  - mujoco
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- - arxiv:2610.02089
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- datasets:
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- - snupilab/humanoidtoolbench-teleop
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  ---
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  # HumanoidToolBench DP: Simulation training, 3,003 segments
@@ -39,4 +39,4 @@ This is the DP policy reported in the HumanoidToolBench paper; its success rates
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  Retain run/checkpoints/ckpt_40000 layout. Use HumanoidToolBench native adapter with run directory run and step 40000. Run from exported run directory for explicit dataset_statistics.json resolution; serialized normalization bounds are retained. Nearby launch.json contains required exact language-conditioning receipt. Install pinned Psi0 source plus HumanoidToolBench adapter and pre-cache openai/clip-vit-large-patch14 at 32bd64288804d66eefd0ccbe215aa642df71cc41. DP native serving selects ema_net.pth; model.safetensors is retained for launcher discovery. Do not substitute non-EMA weights.
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- Training uses independent model optimizers and shared GPU execution through MPS. Publication is performed by a CPU uploader after final checkpoint validation.
 
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  ---
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+ datasets:
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+ - snupilab/humanoidtoolbench-teleop
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  language:
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  - en
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  tags:
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  - robotics
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  - humanoidtoolbench
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  - mujoco
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+ pipeline_tag: robotics
 
 
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  ---
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  # HumanoidToolBench DP: Simulation training, 3,003 segments
 
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  Retain run/checkpoints/ckpt_40000 layout. Use HumanoidToolBench native adapter with run directory run and step 40000. Run from exported run directory for explicit dataset_statistics.json resolution; serialized normalization bounds are retained. Nearby launch.json contains required exact language-conditioning receipt. Install pinned Psi0 source plus HumanoidToolBench adapter and pre-cache openai/clip-vit-large-patch14 at 32bd64288804d66eefd0ccbe215aa642df71cc41. DP native serving selects ema_net.pth; model.safetensors is retained for launcher discovery. Do not substitute non-EMA weights.
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+ Training uses independent model optimizers and shared GPU execution through MPS. Publication is performed by a CPU uploader after final checkpoint validation.