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Release real-time motion planning artifacts on Hugging Face#1

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@NielsRogge

Hi @korbinianmoller 馃

I'm Niels and work as part of the open-source team at Hugging Face. I discovered your work on Arxiv and was wondering whether you would like to submit it to hf.co/papers to improve its discoverability. If you are one of the authors, you can submit it at https://huggingface.co/papers/submit.

The paper page lets people discuss about your paper and lets them find artifacts about it (your models or code 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 your GitHub README that the code for your real-time motion planning algorithm is "coming soon". Would you like to host the code and any associated artifacts (like pre-trained configuration benchmarks or checkpoints) on https://huggingface.co/models? Hosting on Hugging Face will give your work more visibility and enable better discoverability. We can add tags so that people find the models easier, link it to the paper page, etc.

If you're down, leaving a guide here. For custom implementations, you can use the PyTorchModelHubMixin class which adds from_pretrained and push_to_hub to the model, or simply use hf_hub_download to allow users to easily download your files.

After uploaded, we can also link the models to the paper page (here) so people can discover your work.

You can also build a demo for your planner on Spaces, where we can provide you with a ZeroGPU grant for hardware acceleration if needed.

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

Kind regards,

Niels

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