Make sure download metrics work on HF, add better discoverability

[NielsRogge]

Dear authors,

I noticed your awesome repository trending on paperswithcode. I'm from Hugging Face, and I see all checkpoints are on 🤗
already, but present in a single repository, which means download metrics won't work. 😞

This PR resolves that by showcasing the PyTorchModelHubMixin class, which is a minimal class that allows to easily add functionalities like from_pretrained, save_pretrained, and push_to_hub to any custom nn.Module!

Similar to models in the Transformers/Diffusers library, it allows to push and reload models in the format of safetensors (for the weights) and a config.json (for the model's configuration). It also creates an automated model card, along with tags for better discoverability of your models. Usage is as follows:

from models.voicecraft import VoiceCraftHF

model = VoiceCraftHF.from_pretrained(f"nielsr/{voicecraft_name}")

The corresponding model is here for now: https://huggingface.co/nielsr/gigaHalfLibri330M_TTSEnhanced_max16s, but I could transfer it (along with the other checkpoints) to your organization.

This ensures:
✅ download metrics will work for you
✅ tags are added to the model card automatically which means people can easier find the models on the hub (better discoverability)
✅ reloading the model is just a single line of code

Here's a notebook regarding how I did that :)

Btw, there's no need for a wget in the demo notebooks, you can leverage hf_hub_download to load a file in a single line of code! This is also illustrated in my notebook above.

Would you be interested in this integration?

Kind regards,

Niels
ML @ HF

[NielsRogge]

Hi @jasonppy thanks for merging my PR! 🙌

Would you be up for pushing the various checkpoints to separate repos on the hub as done in this PR? This way download metrics will work

Also, feel free to leverage hf_hub_download rather than wget as it's easier to download checkpoints