Hi @1anj 🤗
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 saw in your GitHub README that the model checkpoints for DeepMoLM are "coming soon." It's great to see that you've already hosted the SAM/CLIP component checkpoints on the Hub (pkulium/sam_clip_ckpt)! Would you like to also host the full pre-trained DeepMoLM models on https://huggingface.co/models when 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 it 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, which lets you to upload the model and allows people to download and use them right away.
You can also build a demo for your model on Spaces, and we can provide you a ZeroGPU grant, which gives you free access to A100 GPUs for the community.
Let me know if you're interested or need any guidance :)
Kind regards,
Niels
Hi @1anj 🤗
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 saw in your GitHub README that the model checkpoints for DeepMoLM are "coming soon." It's great to see that you've already hosted the SAM/CLIP component checkpoints on the Hub (
pkulium/sam_clip_ckpt)! Would you like to also host the full pre-trained DeepMoLM models on https://huggingface.co/models when 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 it 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, which lets you to upload the model and allows people to download and use them right away.You can also build a demo for your model on Spaces, and we can provide you a ZeroGPU grant, which gives you free access to A100 GPUs for the community.
Let me know if you're interested or need any guidance :)
Kind regards,
Niels