Hi @FraunhoferMEVIS 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 your GitHub repository link.
Would you like to host the foundation models you've pre-trained (including the Whole Slide Concepts model and the UNICORN encoder) on https://huggingface.co/models? Hosting on Hugging Face will give your work more visibility and enable better discoverability within the medical imaging community. We can add specific tags like "pathology" so that people find the models easier and link them directly to the paper page.
If you're down, leaving a guide here. Since this project uses PyTorch, you could leverage the PyTorchModelHubMixin class which adds from_pretrained and push_to_hub to your models, allowing researchers to download and use them instantly. Alternatively, you can upload weights through the UI/CLI and users can use hf_hub_download.
After uploaded, we can also link the models to the paper page (read here) so people can discover your work.
Let me know if you're interested or need any guidance! :)
Kind regards,
Niels
Hi @FraunhoferMEVIS 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 your GitHub repository link.
Would you like to host the foundation models you've pre-trained (including the Whole Slide Concepts model and the UNICORN encoder) on https://huggingface.co/models? Hosting on Hugging Face will give your work more visibility and enable better discoverability within the medical imaging community. We can add specific tags like "pathology" so that people find the models easier and link them directly to the paper page.
If you're down, leaving a guide here. Since this project uses PyTorch, you could leverage the PyTorchModelHubMixin class which adds
from_pretrainedandpush_to_hubto your models, allowing researchers to download and use them instantly. Alternatively, you can upload weights through the UI/CLI and users can use hf_hub_download.After uploaded, we can also link the models to the paper page (read here) so people can discover your work.
Let me know if you're interested or need any guidance! :)
Kind regards,
Niels