Niels here from the open-source team at Hugging Face. I found your work through ECCV (congrats!), and indexed your paper here: https://huggingface.co/papers/2403.00628, congrats on getting it accepted to ECCV (feel free to claim authorship with your HF account). I work together with AK on improving the visibility of researchers' work on the hub.
I was wondering you'd be up for collaborating on releasing the checkpoints on the š¤ hub, rather than Google Drive, to improve their discoverability. We can add tags so that people find them when filtering https://huggingface.co/models.
Uploading models
See here for a guide: https://huggingface.co/docs/hub/models-uploading. In case the models are custom PyTorch model, we could probably leverage the PyTorchModelHubMixin class which adds from_pretrained and push_to_hub to each model. Alternatively, one can leverages the hf_hub_download one-liner to download a checkpoint from the hub.
We encourage researchers to push each model checkpoint to a separate model repository, so that things like download stats also work. Moreover, we can then link the checkpoints to the paper page, improving their visibility.
Let me know if you're interested/need any help regarding this!
Hi @GityuxiLiu,
Niels here from the open-source team at Hugging Face. I found your work through ECCV (congrats!), and indexed your paper here: https://huggingface.co/papers/2403.00628, congrats on getting it accepted to ECCV (feel free to claim authorship with your HF account). I work together with AK on improving the visibility of researchers' work on the hub.
I was wondering you'd be up for collaborating on releasing the checkpoints on the š¤ hub, rather than Google Drive, to improve their discoverability. We can add tags so that people find them when filtering https://huggingface.co/models.
Uploading models
See here for a guide: https://huggingface.co/docs/hub/models-uploading. In case the models are custom PyTorch model, we could probably leverage the PyTorchModelHubMixin class which adds
from_pretrainedandpush_to_hubto each model. Alternatively, one can leverages the hf_hub_download one-liner to download a checkpoint from the hub.We encourage researchers to push each model checkpoint to a separate model repository, so that things like download stats also work. Moreover, we can then link the checkpoints to the paper page, improving their visibility.
Let me know if you're interested/need any help regarding this!
Cheers,
Niels ML Engineer @ HF š¤