Release MemFlow on Hugging Face

Hi @so-link 🤗

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 model you've pre-trained on https://huggingface.co/models? 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.

I noticed in your paper that the code is intended to be released at https://github.com/so-link/MemFlow, though it currently appears to be unavailable. When you are ready to release it, hosting on Hugging Face would be a great way to showcase the MemFlow framework.

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

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

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

No repository files, tests, or entry points are identified. Start by determining whether the authors intend to publish the paper and pretrained model on Hugging Face and what artifact is available; done would require a released model linked to its paper page, or an explicit decision not to proceed.