Niels here from the open-source team at Hugging Face. I discovered your work through the paper page: https://huggingface.co/papers/2407.15060 (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.
Secondly, the download stats don't work for your model since the repository does not contain a config.json.
We recommend leveraging the PyTorchModelHubMixin to push your model to the hub and reload it using from_pretrained. This ensures a config.json along with safetensors weights are pushed to the hub.
Hi,
Niels here from the open-source team at Hugging Face. I discovered your work through the paper page: https://huggingface.co/papers/2407.15060 (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.
Add a model card
I see the model is already on the hub: https://huggingface.co/Cyan0731/MusiConGen, however it currently has no model card. Would be great to add one!
See here: https://huggingface.co/docs/hub/en/model-cards.
Moreover, the model could be linked with the paper, see here on how to do that: https://huggingface.co/docs/hub/en/model-cards#linking-a-paper
Ensuring downloads work
Secondly, the download stats don't work for your model since the repository does not contain a config.json.
We recommend leveraging the PyTorchModelHubMixin to push your model to the hub and reload it using
from_pretrained. This ensures a config.json along withsafetensorsweights are pushed to the hub.Alternatively, we offer https://huggingface.co/docs/transformers/custom_models which ensures your model can be loaded using Transformers, with
trust_remote_code=True.Let me know if you need any help regarding this!
Cheers,
Niels ML Engineer @ HF 🤗