Hi @SteveZeyuZhang 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 yours got featured: https://huggingface.co/papers/2606.01788.
The paper page lets people discuss about your paper and lets them find artifacts about it (your models 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.
I noticed in your project page's source code that you have a placeholder for a Hugging Face model repository (AIGeeksGroup/PlatonicNav). Would you like to host the PlatonicNav weights or framework components on https://huggingface.co/models?
Hosting on Hugging Face will give your work more visibility and enable better discoverability. We can add tags (like robotics) in the model cards so that people find the models easier and link it directly to the paper page.
If you're down, leaving a guide here. If it's a custom PyTorch-based setup, you can use the PyTorchModelHubMixin
class which adds from_pretrained and push_to_hub to the model, or simply use hf_hub_download to allow users to easily download your PTM weights.
You can also build a demo for your model on Spaces, we can provide you a ZeroGPU grant, which gives you free GPU-backed compute for eligible demo Spaces.
Let me know if you're interested/need any guidance :)
Kind regards,
Niels
Hi @SteveZeyuZhang 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 yours got featured: https://huggingface.co/papers/2606.01788.
The paper page lets people discuss about your paper and lets them find artifacts about it (your models 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.
I noticed in your project page's source code that you have a placeholder for a Hugging Face model repository (
AIGeeksGroup/PlatonicNav). Would you like to host the PlatonicNav weights or framework components on https://huggingface.co/models?Hosting on Hugging Face will give your work more visibility and enable better discoverability. We can add tags (like
robotics) in the model cards so that people find the models easier and link it directly to the paper page.If you're down, leaving a guide here. If it's a custom PyTorch-based setup, you can use the PyTorchModelHubMixin
class which adds
from_pretrainedandpush_to_hubto the model, or simply use hf_hub_download to allow users to easily download your PTM weights.You can also build a demo for your model on Spaces, we can provide you a ZeroGPU grant, which gives you free GPU-backed compute for eligible demo Spaces.
Let me know if you're interested/need any guidance :)
Kind regards,
Niels