Hi @chriskoo 🤗
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/2602.01418.
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.
Would you like to host the PaPE model checkpoints you've pre-trained (for ImageNet, COCO, UCF101, and the event-based models) on https://huggingface.co/models?
I saw in your GitHub README that you're currently hosting weights on a DTU data repository. Hosting on Hugging Face will give you more visibility and enable better discoverability. We can add metadata tags (like object-detection or video-classification) so that people find the models easier, link them to the paper page, etc.
If you're down, leaving a guide here. For custom PyTorch models like yours, you can use the PyTorchModelHubMixin class which adds from_pretrained and push_to_hub to the model which lets you to upload the model and people to download and use models right away. Alternatively, if you prefer to just upload the .pt files through the UI, people can also use hf_hub_download.
After uploaded, we can also link the models 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
Hi @chriskoo 🤗
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/2602.01418.
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.
Would you like to host the PaPE model checkpoints you've pre-trained (for ImageNet, COCO, UCF101, and the event-based models) on https://huggingface.co/models?
I saw in your GitHub README that you're currently hosting weights on a DTU data repository. Hosting on Hugging Face will give you more visibility and enable better discoverability. We can add metadata tags (like object-detection or video-classification) so that people find the models easier, link them to the paper page, etc.
If you're down, leaving a guide here. For custom PyTorch models like yours, you can use the PyTorchModelHubMixin class which adds
from_pretrainedandpush_to_hubto the model which lets you to upload the model and people to download and use models right away. Alternatively, if you prefer to just upload the.ptfiles through the UI, people can also use hf_hub_download.After uploaded, we can also link the models 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