Hi @yifai 🤗
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/2512.07805.
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.
Your abstract mentions that "Our code and weights are available at this https URL", referring to your GitHub repository (https://github.com/model-architectures/GRAPE). While the code for implementing and training models with GRAPE is available, I couldn't find direct download links for the pre-trained GRAPE-A and GRAPE-M model checkpoints (e.g., Medium Model, Large Model) that are evaluated in the paper.
Would you be interested in hosting these pre-trained model checkpoints 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 models easier, link them to the paper page, etc.
If you're interested, here's a guide: 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 methods, making it easy to upload and for others to download and use your models. Alternatively, people can also use hf_hub_download to download models directly from the Hub.
After uploading, we can also link the models to the paper page (read here) so people can discover your work.
You can also build a demo for your model on Spaces, and we can provide you a ZeroGPU grant, which gives you A100 GPUs for free.
Let me know if you're interested or need any guidance!
Kind regards,
Niels
Hi @yifai 🤗
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/2512.07805.
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.
Your abstract mentions that "Our code and weights are available at this https URL", referring to your GitHub repository (https://github.com/model-architectures/GRAPE). While the code for implementing and training models with GRAPE is available, I couldn't find direct download links for the pre-trained GRAPE-A and GRAPE-M model checkpoints (e.g., Medium Model, Large Model) that are evaluated in the paper.
Would you be interested in hosting these pre-trained model checkpoints 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 models easier, link them to the paper page, etc.
If you're interested, here's a guide: 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_hubmethods, making it easy to upload and for others to download and use your models. Alternatively, people can also use hf_hub_download to download models directly from the Hub.After uploading, we can also link the models to the paper page (read here) so people can discover your work.
You can also build a demo for your model on Spaces, and we can provide you a ZeroGPU grant, which gives you A100 GPUs for free.
Let me know if you're interested or need any guidance!
Kind regards,
Niels