Hi @mason-ching 🤗
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 and project page URLs.
I noticed in your GitHub repository for A3-FPN that the model weight links in the results tables are currently placeholders. Would you like to host the model checkpoints you've trained 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 (like object-detection or image-segmentation) so that people find the models easier, link them to the paper page, etc.
If you're down, leaving a guide here. If it's a custom PyTorch model (or based on mmdetection/detectron2), you can simply upload the weights and a model card. You can even use the PyTorchModelHubMixin class to add from_pretrained and push_to_hub functionality.
After uploaded, we can also link the models to the paper page (read here) so people can discover your work.
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 or need any guidance!
Kind regards,
Niels
Hi @mason-ching 🤗
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 and project page URLs.
I noticed in your GitHub repository for A3-FPN that the model weight links in the results tables are currently placeholders. Would you like to host the model checkpoints you've trained 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 (like
object-detectionorimage-segmentation) so that people find the models easier, link them to the paper page, etc.If you're down, leaving a guide here. If it's a custom PyTorch model (or based on mmdetection/detectron2), you can simply upload the weights and a model card. You can even use the PyTorchModelHubMixin class to add
from_pretrainedandpush_to_hubfunctionality.After uploaded, we can also link the models to the paper page (read here) so people can discover your work.
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 or need any guidance!
Kind regards,
Niels