Release Robot Control Stack model weights on Hugging Face

[NielsRogge]

Hi @juelg 🤗

Niels here from the open-source team at Hugging Face. I discovered your work through Hugging Face's daily papers as yours got featured: https://huggingface.co/papers/2509.14932.
The paper page lets people discuss about your paper and lets them find artifacts about it (your models, datasets or demo for instance), you can also claim
the paper as yours which will show up on your public profile at HF, add Github and project page URLs.

It's great to see that you've already started hosting datasets like rcs_utn_green_box_v1 on the 🤗 hub under the RobotControlStack organization!

I noticed in the abstract that you've also released the weights for the fine-tuned VLA models (Octo, OpenVLA, Pi Zero) evaluated in the paper. It'd be awesome to also make these checkpoints available on the hub to improve their discoverability and visibility. We can add tags so that people find them when filtering https://huggingface.co/models and link them directly to the paper page.

Uploading models

See here for a guide: https://huggingface.co/docs/hub/models-uploading.

In this case, we could leverage the PyTorchModelHubMixin class if you are using PyTorch, which adds from_pretrained and push_to_hub to any custom nn.Module. Alternatively, one can leverage the hf_hub_download one-liner to download a checkpoint from the hub.

We encourage researchers to push each model checkpoint to a separate model repository, so that things like download stats also work. We can then also link the checkpoints to the paper page (read here).

Let me know if you're interested/need any help regarding this!

Cheers,

Niels
ML Engineer @ HF 🤗