Release IPDiff on Hugging Face #1

Hi @MathLee 🤗

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, and add GitHub and project page URLs.

I saw on your GitHub repository that the code and pre-trained checkpoints for IPDiff are coming soon! Would you like to host the pre-trained checkpoints on https://huggingface.co/models when they are ready?

Hosting on Hugging Face will give you more visibility/enable better discoverability. We can add tags in the model cards so that people find the models easier, link it to the paper page, etc.

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 allows people to download and use it right away. If you do not want this and directly want to upload the model through the UI, people can also use hf_hub_download.

After uploading, 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, and we can provide you a ZeroGPU grant, which gives you free GPU-backed compute for eligible demo Spaces.

Let me know if you're interested/need any guidance when you are ready to release!

Kind regards,

Niels