Hi @robotic-manipulation 🤗
I'm Niels from the Hugging Face open-source team. I came across your recent work on Arxiv (https://arxiv.org/abs/2309.16085) and was impressed by your novel differentiable robot neural distance function (RNDF) for grasp synthesis. We're reaching out to see if you'd be interested in hosting your pre-trained RNDF models on the Hugging Face Hub.
Hosting your models on Hugging Face would significantly increase their visibility and discoverability within the research community. We can help you create model cards with relevant metadata and link them directly to your paper page on hf.co/papers. This would allow researchers to easily access and utilize your models, contributing to broader adoption and collaboration.
If you're interested, we can guide you through the process of uploading your checkpoints. For PyTorch models, the PyTorchModelHubMixin simplifies uploading and provides from_pretrained functionality. Alternatively, you can upload directly through the Hugging Face UI or use hf_hub_download. We're happy to help with any questions you may have!
Let me know your thoughts!
Kind regards,
Niels
ML Engineer @ Hugging Face 🤗
Hi @robotic-manipulation 🤗
I'm Niels from the Hugging Face open-source team. I came across your recent work on Arxiv (https://arxiv.org/abs/2309.16085) and was impressed by your novel differentiable robot neural distance function (RNDF) for grasp synthesis. We're reaching out to see if you'd be interested in hosting your pre-trained RNDF models on the Hugging Face Hub.
Hosting your models on Hugging Face would significantly increase their visibility and discoverability within the research community. We can help you create model cards with relevant metadata and link them directly to your paper page on hf.co/papers. This would allow researchers to easily access and utilize your models, contributing to broader adoption and collaboration.
If you're interested, we can guide you through the process of uploading your checkpoints. For PyTorch models, the
PyTorchModelHubMixinsimplifies uploading and providesfrom_pretrainedfunctionality. Alternatively, you can upload directly through the Hugging Face UI or usehf_hub_download. We're happy to help with any questions you may have!Let me know your thoughts!
Kind regards,
Niels
ML Engineer @ Hugging Face 🤗