Hi @xgxgnpu 🤗
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 your paper and find related artifacts (such as models and datasets), and you can also claim the paper as yours to show it on your public profile, as well as link your GitHub repository.
I noticed in your GitHub repository that you plan to release the code and data for FS-PIELM upon acceptance of the manuscript.
It would be awesome to host your upcoming pre-trained models and datasets on the 🤗 hub to improve their discoverability and visibility! We can add tags so that people can easily find them when filtering on the Hugging Face Hub.
Uploading models
See here for a guide: https://huggingface.co/docs/hub/models-uploading.
If it's a custom PyTorch model, you can leverage the PyTorchModelHubMixin class, which adds from_pretrained and push_to_hub to any custom nn.Module. Alternatively, you can use the hf_hub_download one-liner to let users easily download checkpoints from the hub.
Uploading dataset
It would also be great to make your PDE datasets available on 🤗, so that people can load them directly:
from datasets import load_dataset
dataset = load_dataset("your-hf-org-or-username/your-dataset")See here for a guide: https://huggingface.co/docs/datasets/loading.
Please let me know if you're interested or if you need any help when the time comes to release your work!
Cheers,
Niels
ML Engineer @ HF 🤗
Hi @xgxgnpu 🤗
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 your paper and find related artifacts (such as models and datasets), and you can also claim the paper as yours to show it on your public profile, as well as link your GitHub repository.
I noticed in your GitHub repository that you plan to release the code and data for FS-PIELM upon acceptance of the manuscript.
It would be awesome to host your upcoming pre-trained models and datasets on the 🤗 hub to improve their discoverability and visibility! We can add tags so that people can easily find them when filtering on the Hugging Face Hub.
Uploading models
See here for a guide: https://huggingface.co/docs/hub/models-uploading.
If it's a custom PyTorch model, you can leverage the PyTorchModelHubMixin class, which adds
from_pretrainedandpush_to_hubto any customnn.Module. Alternatively, you can use the hf_hub_download one-liner to let users easily download checkpoints from the hub.Uploading dataset
It would also be great to make your PDE datasets available on 🤗, so that people can load them directly:
See here for a guide: https://huggingface.co/docs/datasets/loading.
Please let me know if you're interested or if you need any help when the time comes to release your work!
Cheers,
Niels
ML Engineer @ HF 🤗