Release full DRIFT framework code and artifacts on Hugging Face

[NielsRogge]

Hi @leolee99 🤗

Niels here from 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 code, models, datasets or demo 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 saw in your GitHub README that the full code (including other models) for DRIFT will be released later. It would be great to make this full implementation of your framework and any associated components or artifacts available on the 🤗 hub, to improve their discoverability/visibility.
We can add tags so that people find them when filtering https://huggingface.co/models and https://huggingface.co/datasets.

Uploading code/framework

For your code and framework implementation, you can simply upload your repository as a Hugging Face model or dataset repository. For any potential model checkpoints you might release in the future, see here for a guide: https://huggingface.co/docs/hub/models-uploading.
In this case, we could leverage the PyTorchModelHubMixin class which adds from_pretrained and push_to_hub to any custom nn.Module. Alternatively, one can leverages the hf_hub_download one-liner to download a checkpoint from the hub.
We encourage researchers to push each model checkpoint to a separate model repository, so that things like download stats also work. We can then also link the checkpoints to the paper page.

Uploading dataset

If you also plan to release any new datasets with the full code, it would be awesome to make them available on 🤗 , so that people can do:

from datasets import load_dataset

dataset = load_dataset("your-hf-org-or-username/your-dataset")

See here for a guide: https://huggingface.co/docs/datasets/loading.
Besides that, there's the dataset viewer which allows people to quickly explore the first few rows of the data in the browser.

You can also build a demo for your framework on Spaces, we can provide you a ZeroGPU grant, which gives you A100 GPUs for free for community projects.

Let me know if you're interested/need any help regarding this once the full code is ready!

Cheers,

Niels
ML Engineer @ HF 🤗