Release ViViT-SSL on Hugging Face

Hi @EIDOSLAB 🤗

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](https://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.

I noticed in your paper "Cardiac Output Prediction from Echocardiograms" that you plan to release the source code at https://github.com/EIDOSLAB/cardiac-output (though it currently seems to be a work in progress/private). Would you like to host the **ViViT-SSL** model you've pre-trained on https://huggingface.co/models? Hosting on Hugging Face will give you more visibility and enable better discoverability within the medical AI community.

If you're down, leaving a guide [here](https://huggingface.co/docs/hub/models-uploading). If it's a custom PyTorch model, you can use the [PyTorchModelHubMixin](https://huggingface.co/docs/huggingface_hub/package_reference/mixins#huggingface_hub.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.

After uploaded, we can also link the models to the paper page (read [here](https://huggingface.co/docs/hub/en/model-cards#linking-a-paper)) so people can discover your work.

You can also build a demo for your model on [Spaces](https://huggingface.co/spaces), and we can potentially provide you a ZeroGPU [grant](https://huggingface.co/docs/hub/en/spaces-gpus#community-gpu-grants), which gives you A100 GPUs for free.

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

Kind regards,

Niels