YAML Metadata Warning:empty or missing yaml metadata in repo card
Check out the documentation for more information.
0520 pi0.5 + RL Token cotrain (device c)
Cotrained pair on the screw insertion task using device-c data
(Shiki42/0420_0423screw_c + Shiki42/0420_0423screw_critical_c at 1:1).
Layout
model.safetensors(root) — pi0.5 VLA (cotrained, ~3.6 B params bf16, ~14.5 GB)rlt/model.safetensors— RL Token (cotrained, ~256 M params fp32, ~1 GB)
Load
from lerobot.policies.pi05.modeling_pi05 import PI05Policy
from lerobot.policies.rlt.modeling_rlt_token import RLTokenPolicy
from lerobot.policies.rlt.configuration_rlt_token import RLTokenPolicyConfig
from huggingface_hub import snapshot_download
# Download both halves to the same local dir, set vla_pretrained_path to the
# root of that dir, and load the RLT from the rlt/ subfolder.
local = snapshot_download("Shiki42/0520_pi0.5screw_rlt_cotrain_c", repo_type="model")
vla = PI05Policy.from_pretrained(local)
cfg = RLTokenPolicyConfig.from_pretrained(local + "/rlt")
cfg.vla_pretrained_path = local
rlt = RLTokenPolicy.from_pretrained(local + "/rlt", config=cfg)
Provenance
- VLA SFT baseline:
Shiki42/pi05_screw_c_mix_20k(20k-step continued SFT of pi0.5). - RL Token init:
Shiki42/rlt_token_mix_c4_15k(15k-step joint with the SFT baseline). - Restart: from the 15k RLT + SFT baseline VLA, fresh AdamW, c4 hyperparams
(
rl_token_lr=3e-4,vla_lr=1e-5,vla_ft_weight=1.0,norm_gamma=0.5, batch 16, 1:1 mixedscrew_c+screw_critical_c). Stopped early on the rolling-1000 average ofloss_reconreturning to ≤0.215 (the 15k cotrain floor).
- Downloads last month
- 42
Inference Providers NEW
This model isn't deployed by any Inference Provider. 🙋 Ask for provider support