awslabs / awslabs/Agent-EvalKit
Release AgentEvalBench on Hugging Face
- Dominant language
- Python
- Stars
- 38
- Forks
- 7
- PR merge metrics
- No merged PRs in 30d
Description
Hi @sangminwoo 🤗
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/2605.11378.
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 **AgentEvalBench** benchmark you've released on https://huggingface.co/datasets?
I see you're using GitHub for it. Hosting on Hugging Face will give you more visibility/enable better discoverability, and will also allow people to do:
```python
from datasets import load_dataset
dataset = load_dataset("your-hf-org-or-username/AgentEvalBench")
```
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](https://huggingface.co/docs/hub/en/datasets-viewer) which allows people to quickly explore the first few rows of the data (like the evaluation requirements and test scenarios) in the browser.
After uploaded, we can also link the datasets to the paper page (read [here](https://huggingface.co/docs/hub/en/model-cards#linking-a-paper)) so people can discover your work.
Let me know if you're interested/need any guidance.
Kind regards,
Niels
Contributor guide
Research direction
Review the existing AgentEvalBench dataset and repository contents, then read Hugging Face's dataset loading and dataset viewer guides linked in the issue. Confirm whether the project maintainer wants the benchmark hosted on Hugging Face, and define completion as an uploaded dataset that loads with `load_dataset` and is linked from the paper page.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- huggingface, python
- Domain
- data, machine-learning
- Issue type
- Feature
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Quiet
- Clarity
- Needs clarification
- Newbie friendliness
- 35/100