Release OASIS artifacts (models, datasets) on Hugging Face

[NielsRogge]

Hi @yzhperseverance 🤗

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/2606.08548.
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, and add your GitHub and project page URLs.

It'd be great to make the checkpoints and datasets 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 https://huggingface.co/datasets.

Uploading models

I see the paper mentions a hierarchical visuomotor policy (Flow Matching policy). Would you be open to hosting the pre-trained weights on Hugging Face?

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

In this case, we could leverage the PyTorchModelHubMixin class 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.

Uploading datasets

I noticed you're currently using Google Drive to share the OASIS Object and Texture assets. It would be awesome to make these available on 🤗, so that people can easily explore and download them.

Hosting on the Hub allows for:

from datasets import load_dataset

dataset = load_dataset("your-hf-org-or-username/your-dataset")

See here for a guide: https://huggingface.co/docs/datasets/loading.

Besides that, there's the dataset viewer which allows people to quickly explore the data in the browser.

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

Cheers,

Niels
ML Engineer @ HF 🤗