Sharing models through Hugging Face Hub

[omarespejel]

Hi TorchXRayVision team!

This project is amazing! Several Hugging Face followers and members of the "ML for healthcare" community recommended that we contacted you 🤗. I see you host and share models/datasets with your own server. Would you be interested in sharing your models in the Hugging Face Hub?

This integration would allow you to freely download/upload models, and make your work more accessible and visible to the rest of the ML community. We can help you set up a TorchXRayVision organization (examples, Facebook AI y Stanford NLP).

Creating the repos and adding new models should be a relatively straightforward process. This is a step-by-step guide explaining the process in case you're interested. Please let us know if you would be interested and if you have any questions.

Some of the benefits of sharing your models through the Hub would be:

• Presence in the HF Hub might lower the entry of barrier to TorchXRayVision as well as increase its visibility.
  • Repos provide useful metadata about their tasks, languages, metrics, etc that make them discoverable
• versioning, commit history, and diffs.
• multiple features from TensorBoard visualizations, PapersWithCode integration, and more.

Additionally, we have a library to programmatically access repositories (both downloading pretrained models and pushing, with a lot of nice things such as filtering, caching, etc). If we want to try out this integration, I would suggest you add one or two models manually and then use the huggingface_hub library to implement downloading those models programmatically from torchxrayvision. You might want to check our documentation to read more about it.

Relevant references:

• Adding a model to the Hub.
• Integrate your library with the Hub.

Happy to hear your thoughts,

Omar and the Hugging Face team (cc @osanseviero @abidlabs )