Hi @jinzhensheng 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, add Github and project page URLs.
I noticed you've released the DeepScaleR-Preview Dataset on Hugging Face which is fantastic! It would also be beneficial to host your trained models on Hugging Face. This will significantly increase their visibility and allow others to easily use them. We can add relevant tags in the model cards.
If you're interested, a guide on uploading models is available here: https://huggingface.co/docs/hub/models-uploading. For custom PyTorch models, the PyTorchModelHubMixin class simplifies the process. Alternatively, the hf_hub_download function provides a one-liner for downloading checkpoints.
After uploading, we can link your models to the paper page: https://huggingface.co/docs/hub/en/model-cards#linking-a-paper.
Let me know if you have any questions or need further assistance.
Kind regards,
Niels
Hi @jinzhensheng 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, add Github and project page URLs.
I noticed you've released the DeepScaleR-Preview Dataset on Hugging Face which is fantastic! It would also be beneficial to host your trained models on Hugging Face. This will significantly increase their visibility and allow others to easily use them. We can add relevant tags in the model cards.
If you're interested, a guide on uploading models is available here: https://huggingface.co/docs/hub/models-uploading. For custom PyTorch models, the PyTorchModelHubMixin class simplifies the process. Alternatively, the
hf_hub_downloadfunction provides a one-liner for downloading checkpoints.After uploading, we can link your models to the paper page: https://huggingface.co/docs/hub/en/model-cards#linking-a-paper.
Let me know if you have any questions or need further assistance.
Kind regards,
Niels