AMD-AGI / AMD-AGI/AgentKernelArena

Release AgentKernelArena Tasks on Hugging Face

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Dominant language
Python
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118
Forks
14
Avg merge
3d 5h
Merged PRs (30d)
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Description

Hi @AMD-AGI 🤗

I'm Niels and work as part of 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/2605.16819.
The paper page lets people discuss about your paper and lets them find artifacts about it (your dataset 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.

Would you like to host the benchmark tasks from AgentKernelArena you've released on https://huggingface.co/datasets?
I see you're currently hosting them within your GitHub repository. Hosting on Hugging Face will give you more visibility/enable better discoverability, and will also allow people to do:

from datasets import load_dataset

dataset = load_dataset("your-hf-org-or-username/your-dataset")

If you're down, leaving a guide here: https://huggingface.co/docs/datasets/loading.
We also support Webdataset, useful for image/video datasets: https://huggingface.co/docs/datasets/en/loading#webdataset.

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 the datasets to the paper page (read here) so people can discover your work.

Let me know if you're interested/need any guidance.

Kind regards,

Niels

Contributor guide

Open the contributing guide

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.

Research direction

No repository files or tests are named. Start by reviewing the Hugging Face Datasets loading guide and dataset viewer documentation, then determine how the repository's benchmark tasks should be published; done means the tasks are available as a Hugging Face dataset and can be linked to the paper page.

Written by the indexing model from the issue text.

Assessment

Tech stack
huggingface, python
Domain
data
Issue type
Feature
Difficulty
4/5
Estimated time
3-5 days
Activity status
Quiet
Clarity
Needs clarification
Newbie friendliness
35/100

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