Niels here from the open-source team at Hugging Face. I discovered your work through the paper page: https://huggingface.co/papers/2312.14232. I work together with AK on improving the visibility of researchers' work and libraries on the hub.
It'd be great to make the models available on the 🤗 hub, 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.
Hi @wangbinDL,
Niels here from the open-source team at Hugging Face. I discovered your work through the paper page: https://huggingface.co/papers/2312.14232. I work together with AK on improving the visibility of researchers' work and libraries on the hub.
It'd be great to make the models available on the 🤗 hub, 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.
Let me know if you need any help regarding this!
Cheers,
Niels ML Engineer @ HF 🤗