---
language:
- en
license: other
license_name: gemma-terms
license_link: https://huggingface.co/henry13522/Taskanchor/blob/main/LICENSE_GEMMA.txt
pipeline_tag: robotics
tags:
- taskanchor
- pi05
- robomemarena
- jax
- orbax
---

# TaskAnchor–π0.5: RoboMemArena 50k weights

This repository contains the complete inference checkpoint and its required
configuration, tokenizer, and normalization assets. Source code will be
published separately on GitHub; the link will be added here when available.
No benchmark scores are published in this repository.

## Files

```text
50000/
  params/                           # Complete backbone + TaskAnchor, Orbax OCDBT
  assets/robomem_memory.json
  assets/pi05_libero/norm_stats.json
  _CHECKPOINT_METADATA
recipe.json                         # Keep one level above 50000/
tokenizer/paligemma_tokenizer.model
weights_manifest.json               # File hashes and tensor inventory
SHA256SUMS                          # Inference payload checksums
release_manifest.json               # Full publication inventory
LICENSE_GEMMA.txt
NOTICE
```

The inference payload is approximately 10.86 GiB. It contains full model
weights, not an adapter-only delta. The parameters are stored in native
JAX/Orbax OCDBT format; they are not Safetensors. The checkpoint was restored
on CPU and checked for finite values. Optimizer state is not included.

## Download

```bash
hf download henry13522/Taskanchor --local-dir ./Taskanchor
cd Taskanchor
sha256sum -c SHA256SUMS
```

In the matching TaskAnchor inference code, set the checkpoint path to
`/absolute/path/to/Taskanchor/50000` and retain `recipe.json` in its parent.
Set `TASKANCHOR_TOKENIZER_PATH` to the absolute path of the supplied
`tokenizer/paligemma_tokenizer.model`. Normalization is read from the checkpoint
assets. The full checkpoint does not require an additional base-weight
download for inference.

## Configuration

The main view uses `refined = current + offset`, with a 1152→512→1152
projection, eight temporal layers, eight heads, and dropout 0.10. The wrist
view remains a current observation. Images are 224×224. Historical visual
features are pooled to 4×4 tokens per frame. This checkpoint retains a separate
permanent frame0 plus up to 191 history frames, with history stride 10.

Inference predicts 20 actions and executes 10 before replanning. Continuous
progress predictions are mapped to the nearest task-specific stage coordinate
before conditioning, with two decimal places. The 50k snapshot corresponds to
5k adapter-only steps followed by 45k joint steps; the visual encoder remains
frozen. The recorded global training batch is 256. Full numerical settings
are retained in `recipe.json` and the saved checkpoint metadata.

## License

The full pretrained-model checkpoint retains applicable upstream π0.5 /
PaliGemma / Gemma terms. See [LICENSE_GEMMA.txt](LICENSE_GEMMA.txt) and
[NOTICE](NOTICE). The separately published source code uses Apache-2.0;
that source license does not replace the pretrained-weight terms.

Gemma is provided under and subject to the Gemma Terms of Use found at ai.google.dev/gemma/terms

Upstream: [OpenPI](https://github.com/Physical-Intelligence/openpi) and
[RoboMemArena](https://github.com/OpenHelix-Team/RoboMemArena).