Hi @dyccyber 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 for instance), you can also claim the paper as yours which will show up on your public profile at HF, and add GitHub/project page URLs.
I noticed in your GitHub README that you plan to release the trained checkpoints for RaysUp soon. Would you like to host these pre-trained checkpoints on https://huggingface.co/models once they are ready?
Hosting on Hugging Face will give you more visibility and enable better discoverability. We can add tags in the model cards so that people find the models easier, link them directly to the paper page, etc.
If you're down, leaving a guide here. If it's a custom PyTorch model, you can use the PyTorchModelHubMixin class which adds from_pretrained and push_to_hub to the model, allowing you to upload the model and users to download and use it right away. Alternatively, users can also use hf_hub_download to fetch individual files.
After they are uploaded, we can also link the models to the paper page (read here) so people can easily discover your work.
You can also build a demo for your model on Spaces, we can provide you a ZeroGPU grant, which gives you free GPU-backed compute for eligible demo Spaces.
Let me know if you're interested or need any guidance!
Kind regards,
Niels
Hi @dyccyber 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 for instance), you can also claim the paper as yours which will show up on your public profile at HF, and add GitHub/project page URLs.
I noticed in your GitHub README that you plan to release the trained checkpoints for RaysUp soon. Would you like to host these pre-trained checkpoints on https://huggingface.co/models once they are ready?
Hosting on Hugging Face will give you more visibility and enable better discoverability. We can add tags in the model cards so that people find the models easier, link them directly to the paper page, etc.
If you're down, leaving a guide here. If it's a custom PyTorch model, you can use the PyTorchModelHubMixin class which adds
from_pretrainedandpush_to_hubto the model, allowing you to upload the model and users to download and use it right away. Alternatively, users can also use hf_hub_download to fetch individual files.After they are uploaded, we can also link the models to the paper page (read here) so people can easily discover your work.
You can also build a demo for your model on Spaces, we can provide you a ZeroGPU grant, which gives you free GPU-backed compute for eligible demo Spaces.
Let me know if you're interested or need any guidance!
Kind regards,
Niels