Release SurGo-R1 and ResGo on Hugging Face

[NielsRogge]

Hi @jinlab-imvr 🤗

Niels here from the open-source team at Hugging Face. I discovered your work through Hugging Face's daily papers as yours was featured: https://huggingface.co/papers/2602.21706.

The paper page lets people discuss your paper and find artifacts linked to it (your models, datasets, or demos, for instance). You can also claim the paper as yours, which will show up on your public profile at HF, and add GitHub and project page URLs.

I saw in the paper and your GitHub repository that you plan to release the SurGo-R1 model checkpoints and the ResGo benchmark soon. It would be great to make these available on the 🤗 Hub to improve their discoverability and visibility within the medical AI community. We can add tags so that people find them when filtering https://huggingface.co/models and https://huggingface.co/datasets.

Uploading 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 leverage the hf_hub_download one-liner to download a checkpoint from the Hub.

Uploading dataset

It would also be awesome to make the ResGo dataset available on 🤗, so that people can do:

from datasets import load_dataset

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

Besides that, there's the dataset viewer which allows people to quickly explore the surgical frames and rationales directly in the browser.

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

Cheers,

Niels
ML Engineer @ HF 🤗