Release DiffPlace code and models on Hugging Face

[NielsRogge]

Hi @HySonLab 🤗

I'm Niels and work as part of the open-source team at Hugging Face. I discovered your work on Arxiv and your paper "DiffPlace: A Conditional Diffusion Framework for Simultaneous VLSI Placement Beyond Sequential Paradigms" caught my attention. Your paper is featured on Hugging Face's paper pages: https://huggingface.co/papers/2510.15897. The paper page lets people discuss your work and find related artifacts. 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.

Your abstract mentions that your source code is publicly available at https://github.com/HySonLab/DiffPlace/, but I noticed the repository's README currently provides no details about how to access or use the DiffPlace framework or any potential pre-trained model checkpoints.

We'd be keen to help you make your DiffPlace code and any associated pre-trained model checkpoints available on the Hugging Face Hub (huggingface.co/models) once they are ready. This would greatly improve their discoverability and visibility within the AI community.

Hosting on Hugging Face will give you more visibility/enable better discoverability. We can add tags in the model cards so that people find the models easier, link it to the paper page, etc.

If you're interested in hosting your models, 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 to the model, letting you upload it and people to download and use models right away. Alternatively, people can download individual files using 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, and we can provide you a ZeroGPU grant, which gives you A100 GPUs for free.

Let me know if you're interested/need any guidance :)

Kind regards,

Niels
ML Engineer @ HF 🤗