Hello,
I'm Niels and work as part of the open-source team at Hugging Face. I discovered your work through Hugging Face Daily Papers: https://huggingface.co/papers/2607.28362
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 saw on your GitHub that the code and model weights are currently being cleaned up and will be released soon. Once they are ready, would you like to host the pre-trained model on https://huggingface.co/models?
Hosting on Hugging Face will give you more visibility and enable better discoverability. We can add tags in the model cards so that people find the model easier, link it to the paper page, etc.
If you're interested, here is a guide for uploading models: https://huggingface.co/docs/hub/models-uploading. If it's a custom PyTorch model, you can use the PyTorchModelHubMixin class which adds from_pretrained and push_to_hub to the model, allowing you to upload and people to download and use models right away.
After uploading, we can link the model to the paper page so people can discover your work. You can also build a demo for your model on Spaces with ZeroGPU for free compute.
Let me know if you're interested/need any guidance!
Kind regards,
Niels
Hello,
I'm Niels and work as part of the open-source team at Hugging Face. I discovered your work through Hugging Face Daily Papers: https://huggingface.co/papers/2607.28362
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 saw on your GitHub that the code and model weights are currently being cleaned up and will be released soon. Once they are ready, would you like to host the pre-trained model on https://huggingface.co/models?
Hosting on Hugging Face will give you more visibility and enable better discoverability. We can add tags in the model cards so that people find the model easier, link it to the paper page, etc.
If you're interested, here is a guide for uploading models: https://huggingface.co/docs/hub/models-uploading. If it's a custom PyTorch model, you can use the PyTorchModelHubMixin class which adds
from_pretrainedandpush_to_hubto the model, allowing you to upload and people to download and use models right away.After uploading, we can link the model to the paper page so people can discover your work. You can also build a demo for your model on Spaces with ZeroGPU for free compute.
Let me know if you're interested/need any guidance!
Kind regards,
Niels