Release ResAdapt artifacts (models, datasets) on Hugging Face

[NielsRogge]

Hi @Xnhyacinth 🤗

Niels here from the open-source team at Hugging Face. I discovered your work through Hugging Face's daily papers as yours got featured: https://huggingface.co/papers/2603.28610.
The paper page lets people discuss about your paper and lets them find artifacts about it (your 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 noticed in your GitHub README that you have placeholders for Hugging Face model and dataset badges. It'd be great to make the trained ResAdapt Allocator checkpoints and the pre-processed datasets (those parquet files) available on the 🤗 hub to improve their discoverability and visibility!

Uploading models

See here for a guide: https://huggingface.co/docs/hub/models-uploading.

In this case, since you are coupling a lightweight Allocator with an unchanged MLLM backbone, you 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.

Uploading dataset

Would be awesome to make the pre-processed Parquet datasets 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.

Let me know if you're interested/need any help regarding this!

Cheers,

Niels
ML Engineer @ HF 🤗