Hi @Jize1 馃
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 your paper on GTA-2 got featured: https://huggingface.co/papers/2604.15715.
The paper page lets people discuss your work and find related artifacts. You can also claim the paper as yours so it shows up on your public profile, and add your Github and project page URLs.
I saw in your README that while the original GTA was released on Hugging Face, the new GTA-Workflow and the updated GTA-Atomic datasets are currently hosted via Github Releases as zip files. Would you like to host these datasets on https://huggingface.co/datasets?
Hosting on Hugging Face will give your benchmark more visibility and enable better discoverability through metadata tags. It also allows people to easily load the data:
from datasets import load_dataset
dataset = load_dataset("open-compass/GTA-Workflow")Besides that, there's the dataset viewer which allows people to quickly explore the multimodal queries and tool-use contexts directly in the browser.
After uploading, we can also link the datasets to the paper page (read here) so people can discover your work more easily.
Let me know if you're interested or need any guidance!
Kind regards,
Niels
ML Engineer @ HF 馃
Hi @Jize1 馃
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 your paper on GTA-2 got featured: https://huggingface.co/papers/2604.15715.
The paper page lets people discuss your work and find related artifacts. You can also claim the paper as yours so it shows up on your public profile, and add your Github and project page URLs.
I saw in your README that while the original GTA was released on Hugging Face, the new GTA-Workflow and the updated GTA-Atomic datasets are currently hosted via Github Releases as zip files. Would you like to host these datasets on https://huggingface.co/datasets?
Hosting on Hugging Face will give your benchmark more visibility and enable better discoverability through metadata tags. It also allows people to easily load the data:
Besides that, there's the dataset viewer which allows people to quickly explore the multimodal queries and tool-use contexts directly in the browser.
After uploading, we can also link the datasets to the paper page (read here) so people can discover your work more easily.
Let me know if you're interested or need any guidance!
Kind regards,
Niels
ML Engineer @ HF 馃