Release Stand-In artifacts (model, dataset) on Hugging Face #8

Hi @BowenXue 🤗

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/2508.07901.
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.

It's fantastic to see that the Stand-In_Wan2.1-T2V-14B_153M_v1.0 model is already available on the 🤗 Hub! We've noted from your TODO list that you also plan to:

1. Open-source model weights compatible with Wan2.2-T2V-A14B.
2. Release the training dataset, data preprocessing scripts, and training code.

It'd be great to make these additional artifacts available on the 🤗 hub too, to further 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 models (Wan2.2-T2V-A14B)

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 (training dataset)

Would be awesome to make the training 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.

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 🤗