InternRobotics / InternRobotics/InternScenes

Link InternScenes dataset and inquire about models on Hugging Face

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Python
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Description

Hi @MarjordCpz 🤗

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/2509.10813.
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 formally link the InternScenes dataset (which I see is already on the 🤗 hub at https://huggingface.co/datasets/InternRobotics/InternScenes) to your paper page, to improve its discoverability/visibility.
We can add tags so that people find it when filtering https://huggingface.co/datasets.

After it's linked, people can easily load it using:

from datasets import load_dataset

dataset = load_dataset("InternRobotics/InternScenes")

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.

I also noted from your abstract that you plan to open-source models as well. Are there any updates on when we can expect the model checkpoints to be released? We'd be happy to help host them on the Hugging Face models hub too!

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

Cheers,

Niels
ML Engineer @ HF 🤗

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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.
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Research direction

No repository files, tests, or entry points are identified. Start by reviewing the repository and the linked InternScenes dataset and paper pages to determine whether any project-side change is expected. Done would require a defined, completed link or metadata update and a clear resolution for the model-checkpoint question.

Written by the indexing model from the issue text.

Assessment

Tech stack
huggingface, python
Domain
data, documentation, machine-learning
Issue type
Feature
Difficulty
4/5
Estimated time
3-5 days
Activity status
Stale
Clarity
Needs clarification
Newbie friendliness
25/100

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