Hi @nathanhhughes 馃
Niels here from the open-source team at Hugging Face. I discovered your work on Arxiv (Hydra++) 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/2607.09455
The paper page lets people discuss your paper and find artifacts linked to it (such as models or datasets). You can also claim the paper, which will show up on your public profile, and link your Github repository and project page.
I saw on the project page that the Hydra++ code will be integrated into the main Hydra repository soon. When that happens, would you be interested in hosting any associated trained models (such as GNN-based room classifiers, descriptors, or shape estimators) on the Hugging Face Hub (https://huggingface.co/models)?
Hosting on Hugging Face offers excellent visibility, and we can link the models directly to your paper page so that other researchers can easily find and run them.
If you're down, leaving a guide here. If you use PyTorch, you can easily leverage the PyTorchModelHubMixin class which adds from_pretrained and push_to_hub to your PyTorch models. Alternatively, one can use the hf_hub_download one-liner to download checkpoints from the hub.
Let me know if you're interested or if you need any guidance when the integration is ready!
Kind regards,
Niels
ML Engineer @ HF 馃
Hi @nathanhhughes 馃
Niels here from the open-source team at Hugging Face. I discovered your work on Arxiv (Hydra++) 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/2607.09455
The paper page lets people discuss your paper and find artifacts linked to it (such as models or datasets). You can also claim the paper, which will show up on your public profile, and link your Github repository and project page.
I saw on the project page that the Hydra++ code will be integrated into the main Hydra repository soon. When that happens, would you be interested in hosting any associated trained models (such as GNN-based room classifiers, descriptors, or shape estimators) on the Hugging Face Hub (https://huggingface.co/models)?
Hosting on Hugging Face offers excellent visibility, and we can link the models directly to your paper page so that other researchers can easily find and run them.
If you're down, leaving a guide here. If you use PyTorch, you can easily leverage the PyTorchModelHubMixin class which adds
from_pretrainedandpush_to_hubto your PyTorch models. Alternatively, one can use the hf_hub_download one-liner to download checkpoints from the hub.Let me know if you're interested or if you need any guidance when the integration is ready!
Kind regards,
Niels
ML Engineer @ HF 馃