Hugging Face Hub Integration

[osanseviero]

Hi there!

This project is super cool! Would you be interested in sharing the pretrained models in the Hugging Face Hub? The Hugging Face Hub offers free hosting of models (over 10,000 models have been uploaded by many research organizations) and it would make your work more accessible and visible to others. People would be able to try the model directly in the browser (we're implementing an image captioning widget at the moment). The only thing required would be to upload the models to the Hub. I'm happy to answer any questions about this.

Happy to hear your thoughts,
Omar

[saahiluppal]

Hello Omar,

I would be really interested in sharing the pretrained models in the Hugging Face Hub.

But due to computation constrain, i have not trained the model to it's full potential. I've trained this model just for 30 epochs, but it needs to train for atleast 200 epochs to reach good accuracy. (and it took me more than a week just to provide this 30 epoch baseline on Tesla P100 GPU)

Best wishes,
Sahil Uppal

[osanseviero]

Hi Sahil!

Thanks for explaining. Even if they checkpoints are not at the full potential, uploading the ones in releases might already be of interest for the community. The Hub repos are versioned, so you can always update them with new ones if you are able to train them more.

Cheers,
Omar

[saahiluppal]

All set then. Can you make me aware of next steps?

[osanseviero]

I would suggest to do the following

1. Create an account http://hf.co/
2. (optional) create an organization for catr (if not, you can just upload the models to your account)
3. For each model, create a model repo and upload the weights (and any needed config if any).

At this point, your models are already shareable. The next point would be a better integration with the library. We have a step-by-step guide depending on what you want to achieve: https://github.com/huggingface/huggingface_hub/blob/main/docs/adding-a-library.md. There are 3 things that can be done

• Downstream support, meaning from your library you can easily load any catr model from the Hub
• Upstream support, meaning anyone can upload catr model to the Hub. I personally don't think this will be needed for this integration
• Inference API, allowing us to use the widget. This should be straightforward after the downstream support and I'm happy to do it.

Let me know if you have any questions!

[saahiluppal]

Seems great. I will do it very soon, and will update you. Then you can integrate it with widget.

Thank you for assistance.
Best