Release RAFM pre-trained checkpoints on Hugging Face

[NielsRogge]

Hi @HiLab-git 🤗

I'm Niels and work as part of the open-source team at Hugging Face. I discovered your work on Arxiv and was wondering whether you would like to submit it to hf.co/papers to improve its discoverability. If you are one of the authors, you can submit it at https://huggingface.co/papers/submit.

The paper page lets people discuss about your paper and lets them find artifacts about it (your models 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.

Would you like to host the pre-trained model checkpoints you've developed for CBCT-to-CT translation on https://huggingface.co/models?
I see you've already released the code for RAFM on GitHub, which is great! However, I didn't see any pre-trained weights available yet. Hosting on Hugging Face will give your work more visibility and enable better discoverability within the medical imaging community. We can add tags in the model cards (like image-to-image) so that people find the models easier and link them directly to the paper page.

If you're down, leaving a guide here. If it's a custom PyTorch model, you can use the PyTorchModelHubMixin class which adds from_pretrained and push_to_hub to the model which lets you upload the model and people to download and use models right away. Alternatively, people can use hf_hub_download.

After uploaded, we can also link the models to the paper page (read here) so people can discover your work.

You can also build a demo for your model on Spaces, we can provide you a ZeroGPU grant, which gives you A100 GPUs for free.

Let me know if you're interested/need any guidance :)

Kind regards,

Niels