Improve discoverability of your work on HF

[NielsRogge]

Hi,

Niels here from the open-source team at Hugging Face. I discovered your work through the paper page: https://huggingface.co/papers/2404.01300 (feel free to claim the paper so that it appears at your HF account!).

However there are a couple of things which could improve the discoverability of your work, which I've listed below.

Upload models and link them to the paper

It would be great to upload the checkpoints to the hub, along with model cards and tags so that people find them when filtering hf.co/models.

See here for a guide: https://huggingface.co/docs/hub/models-uploading. For custom PyTorch models, we recommend leveraging the PyTorchModelHubMixin.

Regarding a model card along with metadata tags, here's a guide: https://huggingface.co/docs/huggingface_hub/en/guides/model-cards

It would be great to link the models to the paper, see here on how to do that: https://huggingface.co/docs/hub/en/model-cards#linking-a-paper

Making the dataset loadable using the datasets library

I see the dataset is uploaded here: https://huggingface.co/datasets/mirshad7/NeRF-MAE, thanks for doing that! However, the repo itself seems empty, there's only a download link in the dataset card. Would you be up for making the dataset loadable using the datasets library? So that people can do:

from datasets import load_dataset

dataset = load_dataset("your-hf-organization/nerf-mae-data")

See here for a guide: https://huggingface.co/docs/datasets/loading

Let me know if you need any help regarding this!

Cheers,

Niels
ML Engineer @ HF 🤗