Release artifacts (models, dataset) on Hugging Face

[NielsRogge]

Hi @pranavnnt 🤗

Niels here from 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, datasets or demo 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.

It'd be great to make the checkpoints and dataset available on the 🤗 hub, to improve their discoverability/visibility within the robotics community. We can add tags so that people find them when filtering https://huggingface.co/models and https://huggingface.co/datasets.

Uploading models

I see the repository includes training scripts for the CLAMP model. Would you like to host the pre-trained weights on Hugging Face as well?

See here for a guide: https://huggingface.co/docs/hub/models-uploading.

In this case, we could leverage the PyTorchModelHubMixin class which adds from_pretrained and push_to_hub to any custom nn.Module. Alternatively, one can leverages the hf_hub_download one-liner to download a checkpoint from the hub.

Uploading dataset

I see you're using Harvard Dataverse for the CLAMP dataset. Hosting it on Hugging Face would allow people to do:

from datasets import load_dataset

dataset = load_dataset("your-hf-org-or-username/CLAMP")

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

Besides that, there's the dataset viewer which allows people to quickly explore the first few rows of the haptic data (and potentially visualize it) directly in the browser.

Let me know if you're interested/need any help regarding this!

Cheers,

Niels
ML Engineer @ HF 🤗