Hacktoberfest 2026: the issues maintainers tagged for October, open and beginner-friendly. Browse Hacktoberfest issues

Release FIRM artifacts (models, datasets) on Hugging Face

Open
  • Is something wrong?
#1 0 comments 0 reactions 0 assignees View on GitHub

Nobody has claimed this yet.

Assessment

Difficulty
4/5
Estimated time
3-5 days
Newbie friendliness
35/100
Issue type
Feature
Clarity
Mostly clear
Activity status
Stale
Tech stack
huggingface, python
Domain
data, machine-learning, release

Research direction

Start by reviewing the listed model and dataset artifacts and the Hugging Face model-uploading and dataset-loading guides linked in the issue. Done means dedicated Hugging Face repositories exist for FIRM-Edit-8B, FIRM-Gen-8B, FIRM-Qwen-Edit, FIRM-SD3.5, FIRM-Edit-370K, and FIRM-Gen-293K, with the artifacts discoverable from the paper page.

Written by the indexing model from the issue text.

Description

Hi @zpy777 🤗

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/2603.12247.
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'd be great to make the checkpoints and datasets available on the 🤗 hub, to improve their discoverability/visibility.
We can add tags so that people find them when filtering https://huggingface.co/models and https://huggingface.co/datasets.

I see that FIRM-Bench is already hosted on Hugging Face (great!). However, for the other models (FIRM-Edit-8B, FIRM-Gen-8B, FIRM-Qwen-Edit, FIRM-SD3.5) and datasets (FIRM-Edit-370K, FIRM-Gen-293K), they are mentioned in a collection. It would be awesome if each of these could have their own dedicated model/dataset repositories for better discoverability and download statistics!

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 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 🤗

Dominant language
Python
Stars
51
Forks
2
No merged PRs in 30d

Getting set up

This project ships no dev container, Dockerfile or contributing guide, so setting up is up to you: start from its README, and see our first-contribution guide for the general steps.

First steps

  1. Read the whole issue, then the project's contributing guide.
  2. Comment on the issue to say you are picking it up — it saves two people doing the same work.
  3. Fork the repository and make your change on a branch.
  4. Open a pull request that references the issue number.

More from VisionXLab/FIRM-Reward

All issues in VisionXLab/FIRM-Reward

Similar issues

More Python issues

Get new issues in your inbox

A short digest of beginner-friendly GitHub issues.