| --- |
| language: |
| - en |
| tags: |
| - robotics |
| - dexterous-manipulation |
| - handson |
| - vision-language-action |
| - world-action-model |
| datasets: |
| - Cyan666/HandsOn-Datasets |
| papers: |
| - 2610.26765 |
| --- |
| |
| # HandsOn: paper multi-task checkpoints |
|
|
| The eight multi-task checkpoints selected in **HandsOn: A Large-Scale Simulation Benchmark for Generalizable Dexterous Manipulation**. |
|
|
| **Upload complete.** All eight model payloads were verified against the source files. See `UPLOAD_VERIFIED.json` and `SHA256SUMS` for per-file verification. |
|
|
| [Paper](https://arxiv.org/abs/2610.26765) · [Code and inference adapters](https://github.com/TsinghuaC3I/HandsOn) · [Dataset](https://huggingface.co/datasets/Cyan666/HandsOn-Datasets) · [Model integration guide](https://github.com/TsinghuaC3I/HandsOn/blob/main/docs/paper-models.md) |
|
|
| | Model | Optimizer step | Checkpoint path | |
| |---|---:|---| |
| | π0.5 | 120,000 | `pi05/120000/` | |
| | DM0.5 | 86,000 | `dm05/checkpoint-86000/` | |
| | HY-Embodied-0.5-VLA | 125,000 | `hy/checkpoint-125000/` | |
| | LingBot-VLA | 151,000 | `lingbot/checkpoint-151000/` | |
| | OpenWAM | 70,000 | `openwam/step-070000/mp_rank_00_model_states.pt` | |
| | FastWAM | 100,000 | `fastwam/step-100000/mp_rank_00_model_states.pt` | |
| | Motus | 100,000 | `motus/step-100000/mp_rank_00_model_states.pt` | |
| | Spatial Forcing | 90,000 | `spatial/90000/` | |
|
|
| These are fixed paper selections, not checkpoints chosen by benchmark success. The single-task DP reference and the prompted GPT-6 controller are outside this weight release. |
|
|
| ## Download |
|
|
| ```bash |
| pip install -U huggingface_hub |
| # One model: |
| hf download Cyan666/HandsOn-Checkpoints --include 'pi05/**' CHECKPOINTS.json --local-dir ./handson-checkpoints |
| # All eight models: |
| hf download Cyan666/HandsOn-Checkpoints --local-dir ./handson-checkpoints |
| ``` |
|
|
| The native checkpoint formats and tensor bytes are preserved. Keep each Orbax `params/` tree and each DCP `state/` tree intact, including hidden metadata files. Standalone π0.5 optimizer state and OpenWAM RNG snapshots are omitted; native DCP and PyTorch containers can still contain training state. File sizes, model steps and relative paths are recorded in `CHECKPOINTS.json`. |
|
|
| ## Inference |
|
|
| Use the matching `--model` profile from the [HandsOn model integration guide](https://github.com/TsinghuaC3I/HandsOn/blob/main/docs/paper-models.md). These are native research checkpoints, not `transformers.AutoModel` packages. The release's adapters preserve checkpoint-specific normalization, image preprocessing, denoising and action horizons. |
|
|
| π0.5 normalization is at `pi05/120000/assets/training_package_final18k.building/norm_stats.json`; Spatial Forcing normalization is at `spatial/90000/assets/v16_eef52/norm_stats.json`. The other adapters use the normalization assets packaged in the code release. |
|
|
| Foundation-model weights, tokenizers, and FastWAM/Motus language caches are supplied separately as documented in the integration guide. Obtain foundation assets from their original publishers and retain their terms. The code provides a language-cache preparation command. |
|
|
| Example, after installing the π0.5 inference environment from the code repository: |
|
|
| ```bash |
| python scripts/serve_paper_policy.py --model pi05 \ |
| --checkpoint /path/to/handson-checkpoints/pi05/120000 \ |
| --normalization /path/to/handson-checkpoints/pi05/120000/assets/training_package_final18k.building/norm_stats.json \ |
| --tokenizer /path/to/paligemma_tokenizer.model |
| ``` |
|
|
| All profiles output absolute physical EEF52 commands, ordered right arm/hand then left arm/hand, for the shared 30 Hz native evaluator. Loading a checkpoint alone does not reproduce the paper's evaluation protocol or certify a new rollout. |
|
|
| ## Provenance and terms |
|
|
| This repository publishes the selected HandsOn finetuning checkpoints in their original formats. Upstream model and component licenses continue to apply; this repository does not replace or broaden those terms. See the [native source notices](https://github.com/TsinghuaC3I/HandsOn/blob/main/docs/policy-source-notices.md) and the relevant foundation-model cards for component-specific information. |
|
|
| The upload verification records file sizes and SHA256 digests. It verifies storage and transfer integrity, not a fresh GPU evaluation or retraining. |
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|
