Instructions to use DecentVLA/pi05_cubestack_fl_client1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- LeRobot
How to use DecentVLA/pi05_cubestack_fl_client1 with LeRobot:
- Notebooks
- Google Colab
- Kaggle
pi0.5 CubeStack -- FedAvg per-client final model (c1)
Final-round local model of client 1 -- manuka: Blue_on_Green, Blue_on_Orange, Orange_on_Green from the 2-client FedAvg run
(examples/pi05_cubestack_fl_explicit.yaml, 30 rounds x 250 local steps). This
is the federated client's weights after its last local update -- the round-29
client state, which was aggregated into the round-30 global model
DecentVLA/pi05_cubestack_fl_2client.
What this is / is not:
- IS: the global FedAvg model adapted to this client's data for 250 local steps in the final round (uses the SHARED pooled-6-repo normalization).
- IS NOT: the from-scratch local-only baseline
DecentVLA/pi05_cubestack_local_c1(that one only ever saw this client's 3 repos, its own 3-repo normalization).
lerobot-native export (portable tokenizer, real 6-D action/state). Deploy like the
other pi0.5 CubeStack models (SO-101, cameras base_0_rgb/left_wrist_0_rgb,
--policy.compile_model=false).
Trained on Isambard-AI (GH200) with decent-vla.
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Model tree for DecentVLA/pi05_cubestack_fl_client1
Base model
lerobot/pi05_base