deploy_public — FastWAM / FlashWAM lift_new policy weights (Franka "pick up the red cube")

Generation-2 weights (2026-07-12) consumed by the sleepmastergx/deploy deployment code (fetch_weights.py downloads gen-2 from here; gen-1 and the shared base pieces — VAE, ActionDiT, T5 text-embed cache — live in SleepMastger/deploy). Layout: runs/<run>/<timestamp>/checkpoints/weights/step_*.pt, each run with its own dataset_stats.json (min/max normalization) and resolved training config.yaml. ⚠️ Always pair a checkpoint with the dataset_stats.json from the SAME run — foreign stats mis-scale actions.

The four runs — deploy with deploy_v2_new/

Trained on SleepMastger/lift_new (103 episodes @ 10 Hz, REAL gripper widths). Contract: execute xyz deltas at 10 Hz; proprio state[6:8] = [w/2, -w/2] (meters). 30 epochs, global batch 32, lr 1e-4 cosine. Five checkpoints per run, named by true epoch (saved every 500 steps at 265 steps/epoch, so most land mid-epoch): epoch_05.7.pt / epoch_09.4.pt / epoch_15.1.pt / epoch_20.8.pt / epoch_30.0.pt. (The last three also exist under their original step names step_002500/005500/007950.) Training loss ≠ robot success in this 103-episode overfitting regime, so A/B the earlier epochs too.

Run	Architecture	Init	Final action loss
runs/lift_new_flashwam_scratch/	FlashWAM M1_FusedKV_RopeFixed (1-layer action expert, fused_kv, fixed RoPE)	Wan2.2-TI2V-5B base + random action expert	0.0155
runs/lift_new_flashwam_ft/	same	LIBERO M1_FusedKV_RopeFixed step_021700 (format-converted)	0.0061
runs/lift_new_fastwam_scratch/	Original FastWAM (30/30 MoT, 6.0B)	Wan2.2 base + ActionDiT interp init	0.0061
runs/lift_new_fastwam_ft/	same	LIBERO release checkpoint	0.0055

FlashWAM (fused_kv) checkpoints require fastwam code at/after commit 8d9e040 (2026-07-08 fused_kv reparameterization) — the vendored copy in the GitHub repo qualifies.

Notes

• The ~18.6 GB Wan2.2-TI2V-5B base DiT is NOT re-hosted — fetched from the public Wan-AI/Wan2.2-TI2V-5B. VAE / ActionDiT / T5 cache: in SleepMastger/deploy (fetch_weights.py assembles everything).
• All policies: two 256² RGB cameras (agentview + wrist), proprio [8], action chunk [32, 7] — xyz delta meters, rpy ≈ 0 (cannot rotate), gripper ±1 after the server-side chain (−1=open, +1=close).
• Training curves: wandb huaweiwam/fastwam-realrobot (runs fpl22etl, xnndko8y, 1ju16696, k42n0ba4).