Release upcoming FireRed-Image-Edit artifacts on Hugging Face

[NielsRogge]

Hi @FireRedTeam 🤗

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/2602.13344.
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 great to see that the FireRed-Image-Edit-1.0 model and a demo are already available on the 🤗 Hub! I also noticed in your GitHub README that you are planning to release other exciting artifacts, specifically:

• FireRed-Image-Edit-1.0-Distilled model (a distilled version of FireRed-Image-Edit-1.0)
• FireRed-Image model (a text-to-image generative model)
• REDEdit-Bench dataset (a comprehensive benchmark for image editing)

It'd be fantastic to help you make these upcoming checkpoints and the dataset available on the 🤗 hub, to further improve their discoverability and visibility.
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.

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 REDEdit-Bench 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 🤗