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hsr-idm-siglip2 – AI Model by FT-LLM-2026-RAMEN | AlphaNeural AI
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FT-LLM-2026-RAMEN
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hsr-idm-siglip2
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robotics
inverse-dynamics
flow-matching
siglip2
HSR
ja
apache-2.0
us
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Model card
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HSR Inverse Dynamics Model (IDM)
Inverse Dynamics Model trained on Toyota HSR robot manipulation episodes.
Architecture
Vision encoder: SigLIP-2 (
google/siglip2-base-patch16-224
, frozen)
Action head: Flow Matching Transformer (4-layer, hidden_dim=512)
Input: (frame_t, frame_t+1) from head + hand cameras → 4 images
Output: action_chunk (H=4 future actions, 8-DOF)
Training
Dataset: 44,892 train / 4,987 val frame-action pairs from approved HSR episodes
50 epochs, AdamW lr=1e-4, cosine+warmup schedule (per-batch stepping)
Mixed precision: BF16
Files
best_model.pt
: Full model checkpoint (weights only, no optimizer state)
action_stats.json
: Action normalization statistics (mean, std, min, max)
