Hi @SizheZhao 馃
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/2609.11561
The paper page lets people discuss 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, and add GitHub and project page URLs.
I saw in the GitHub README that the training/inference code and checkpoints are planned to be released soon. Once the checkpoints are ready, would you like to host the MaP-WAM 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 down, leaving a guide here. If it's a custom PyTorch model, you can use the PyTorchModelHubMixin class which adds from_pretrained and push_to_hub to the model, letting you upload the model and people download and use it right away.
If you do not want this and directly want to upload the model through the UI or however you want, people can also use hf_hub_download.
After uploading, we can also link the models to the paper page (read here) so people can discover your model.
You can also build a demo for your model on Spaces. ZeroGPU gives on-demand GPU-backed compute for demo Spaces. For a limited time, users can create up to two ZeroGPU Spaces in their personal namespace for free.
Let me know if you're interested or need any guidance :)
Kind regards,
Niels
Hi @SizheZhao 馃
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/2609.11561
The paper page lets people discuss 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, and add GitHub and project page URLs.
I saw in the GitHub README that the training/inference code and checkpoints are planned to be released soon. Once the checkpoints are ready, would you like to host the MaP-WAM 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 down, leaving a guide here. If it's a custom PyTorch model, you can use the PyTorchModelHubMixin class which adds
from_pretrainedandpush_to_hubto the model, letting you upload the model and people download and use it right away.If you do not want this and directly want to upload the model through the UI or however you want, people can also use hf_hub_download.
After uploading, we can also link the models to the paper page (read here) so people can discover your model.
You can also build a demo for your model on Spaces. ZeroGPU gives on-demand GPU-backed compute for demo Spaces. For a limited time, users can create up to two ZeroGPU Spaces in their personal namespace for free.
Let me know if you're interested or need any guidance :)
Kind regards,
Niels