Release CoRI artifacts (code, generated communications) on Hugging Face

[NielsRogge]

Hi @jimwang418 🤗

Niels here from the open-source team at Hugging Face. I discovered your work on Arxiv and your project page: https://huggingface.co/papers/2505.20537.

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 on your project page that the code for CoRI is "Coming Soon!". It would be great to make the CoRI framework/code and the dataset of generated communications available on the 🤗 hub once they are ready, to improve their discoverability and visibility.
We can add tags so that people find your work when filtering https://huggingface.co/models and https://huggingface.co/datasets.

Uploading models (CoRI pipeline/code)

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 for any specific model components within your pipeline. Alternatively, one can leverage 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.
You could also consider building a Gradio demo for CoRI on Spaces to showcase your pipeline interactively. We can provide you a ZeroGPU grant, which gives you A100 GPUs for free for research purposes.

Uploading dataset (Generated communications)

It would be awesome to make the dataset of generated communications from your user study available on 🤗 Datasets, 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.

After uploaded, we can also link your repositories to the paper page (read here) so people can easily find your work.

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

Cheers,

Niels
ML Engineer @ HF 🤗