Instructions to use WoWjx/so101-stack3-pi05-baseline with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- LeRobot
How to use WoWjx/so101-stack3-pi05-baseline with LeRobot:
# No code snippets available yet for this library. # To use this model, check the repository files and the library's documentation. # Want to help? PRs adding snippets are welcome at: # https://github.com/huggingface/huggingface.js
- Notebooks
- Google Colab
- Kaggle
SO-101 Stack3 π0.5 baseline checkpoints
This public repository contains five deployment snapshots from one Stack3 fine-tuning run. Checkpoints are stored by optimizer step:
Each checkpoint directory contains the model weights, model configuration, tokenizer, and matching observation/action pre- and post-processors. The optimizer and training-resume state are not included in these deployment snapshots.
Training setup
- Robot: SO-101, single arm; front and wrist RGB cameras
- Observation state: 6 dimensions
- Action: 6 dimensions; first five arm-relative, gripper absolute
- Chunk size: 50; execution horizon: 10 actions
- Precision: BF16; batch size: 64
- Initialization: Stack2 π0.5 checkpoint
004228, followed by Stack3 full-chain fine-tuning - Dataset: 64 Stack3 full-chain episodes (60,481 frames), all used for training; no held-out validation split
- Fine-tune learning rate: peak
1.25e-5, cosine decay to1.25e-6, 1,000-step warmup - Training completed: 10,000 optimizer updates
These are deployment candidates, not a claim of successful three-block stacking. The checkpoints have not been validated on the physical robot. Training loss does not establish real-world task success.
The Stack2 initialization was SO-101 Stack2 π0.5,
checkpoint 004228. No OCBench, FurnitureBench, or OGBench trajectories were
used. The Stack3 dataset and training environment are private and are not
included in this repository.