Release Masked IRL artifacts on Hugging Face

[NielsRogge]

Hi @Minyoung1005 🤗

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/2511.14565.
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.

I noticed that the GitHub repository (https://github.com/MIT-CLEAR-Lab/Masked-IRL) is currently empty and the project page indicates that code and potentially other artifacts will be released soon. It'd be great to make the code for Masked IRL, any trained reward models, and any associated datasets available on the 🤗 hub, to improve their discoverability/visibility once they are ready.
We can add tags so that people find them when filtering https://huggingface.co/models and https://huggingface.co/datasets.

Uploading models (e.g., trained reward models)

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 leverages 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.

Uploading dataset (e.g., experimental data)

Would be awesome to make any new datasets you introduce available on 🤗 , so that people can do:

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 first few rows of the data in the browser.

Let me know if you're interested/need any help regarding this, once your code and artifacts are ready for release!

Cheers,

Niels
ML Engineer @ HF 🤗