Release artifacts (models, dataset) on Hugging Face

[NielsRogge]

Hi @DaehyeonChoi 🤗

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/2512.13250.
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 saw on your GitHub repository (https://github.com/KAIST-Visual-AI-Group/VG-AVS) that you plan to release the code by the fourth week of December. That's fantastic!
It'd be great to make your fine-tuned VLM checkpoints (from your VG-AVS framework) and the new synthetic AVS dataset available on the 🤗 hub, to improve their discoverability/visibility once they are released.
We can add tags so that people find them when filtering https://huggingface.co/models and https://huggingface.co/datasets.

Uploading models

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.
For your fine-tuned VG-AVS models, the pipeline tag would likely be image-text-to-text.

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

Would be awesome to make the AVS dataset 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.
For your synthetic AVS dataset (paired query-target views and Q&A prompts), a relevant task category would be image-text-to-text.

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 once the artifacts are ready for release!

Cheers,

Niels
ML Engineer @ HF 🤗