Hi @eric-ai-lab 🤗
Niels here from the open-source team at Hugging Face. I discovered your exciting work on Arxiv and your GitHub repository for MorphoSim: https://github.com/eric-ai-lab/Morph4D.
I noticed your "TODO" list explicitly includes "Huggingface setup", "Release training code", and "Release inference code". This is great news! We'd be thrilled to help you make your MorphoSim code and any pre-trained model checkpoints available on the 🤗 Hub, to improve their discoverability and visibility once they are ready for release. We can add relevant tags (e.g., text-to-3d or robotics based on your paper) so that people can easily find them when filtering https://huggingface.co/models.
You can also link your work to your paper page (https://huggingface.co/papers/2510.04390) and claim the paper as yours, which will show up on your public profile at HF, and add GitHub and project page URLs.
Uploading models
See here for a guide: https://huggingface.co/docs/hub/models-uploading.
In this case, we could leverage the PyTorchModelHubMixin class which adds from_pretrained and push_to_hub to any custom nn.Module. Alternatively, one can leverage the hf_hub_download one-liner to download a checkpoint from the Hub.
We encourage researchers to push each model checkpoint to a separate model repository, so that things like download stats also work. We can then also link the checkpoints to the paper page.
Gradio Demo on Spaces
I also saw [ ] Gradio Demo in your TODO list! You can build a demo for your model on Spaces. We can provide you a ZeroGPU grant, which gives you A100 GPUs for free for your demo.
Let me know if you're interested/need any help or guidance once you're closer to releasing your artifacts! We'd be happy to assist with your Hugging Face setup.
Cheers,
Niels
ML Engineer @ HF 🤗
Hi @eric-ai-lab 🤗
Niels here from the open-source team at Hugging Face. I discovered your exciting work on Arxiv and your GitHub repository for MorphoSim: https://github.com/eric-ai-lab/Morph4D.
I noticed your "TODO" list explicitly includes "Huggingface setup", "Release training code", and "Release inference code". This is great news! We'd be thrilled to help you make your MorphoSim code and any pre-trained model checkpoints available on the 🤗 Hub, to improve their discoverability and visibility once they are ready for release. We can add relevant tags (e.g.,
text-to-3dorroboticsbased on your paper) so that people can easily find them when filtering https://huggingface.co/models.You can also link your work to your paper page (https://huggingface.co/papers/2510.04390) and claim the paper as yours, which will show up on your public profile at HF, and add GitHub and project page URLs.
Uploading models
See here for a guide: https://huggingface.co/docs/hub/models-uploading.
In this case, we could leverage the PyTorchModelHubMixin class which adds
from_pretrainedandpush_to_hubto any customnn.Module. Alternatively, one can leverage the hf_hub_download one-liner to download a checkpoint from the Hub.We encourage researchers to push each model checkpoint to a separate model repository, so that things like download stats also work. We can then also link the checkpoints to the paper page.
Gradio Demo on Spaces
I also saw
[ ] Gradio Demoin your TODO list! You can build a demo for your model on Spaces. We can provide you a ZeroGPU grant, which gives you A100 GPUs for free for your demo.Let me know if you're interested/need any help or guidance once you're closer to releasing your artifacts! We'd be happy to assist with your Hugging Face setup.
Cheers,
Niels
ML Engineer @ HF 🤗