Hi @gasmichel 馃
I'm Niels and work as part of the open-source team at Hugging Face. I discovered your work through Hugging Face's daily papers as yours got featured: https://huggingface.co/papers/2509.04072.
The paper page lets people discuss about your paper and lets them find artifacts about it (your models 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.
I saw that you've already shared the excellent LibriQuote dataset on the hub, which is a fantastic contribution to the TTS community! Would you also like to host the pre-trained checkpoints for the models you've developed (such as IndexTTS2 and the autoregressive model mentioned in the paper) on https://huggingface.co/models?
Hosting the models on Hugging Face alongside the dataset will give your work even more visibility and enable better discoverability. We can add tags in the model cards so that people find the models easier, and link them directly to the paper page and the dataset.
If you're down, leaving a guide here. If it's a custom PyTorch model, you can use the PyTorchModelHubMixin class which adds from_pretrained and push_to_hub to the model which lets you upload the model and people to download and use models right away. Alternatively, you can use hf_hub_download to download checkpoints.
Let me know if you're interested or need any guidance!
Kind regards,
Niels
Hi @gasmichel 馃
I'm Niels and work as part of the open-source team at Hugging Face. I discovered your work through Hugging Face's daily papers as yours got featured: https://huggingface.co/papers/2509.04072.
The paper page lets people discuss about your paper and lets them find artifacts about it (your models 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.
I saw that you've already shared the excellent LibriQuote dataset on the hub, which is a fantastic contribution to the TTS community! Would you also like to host the pre-trained checkpoints for the models you've developed (such as IndexTTS2 and the autoregressive model mentioned in the paper) on https://huggingface.co/models?
Hosting the models on Hugging Face alongside the dataset will give your work even more visibility and enable better discoverability. We can add tags in the model cards so that people find the models easier, and link them directly to the paper page and the dataset.
If you're down, leaving a guide here. If it's a custom PyTorch model, you can use the PyTorchModelHubMixin class which adds
from_pretrainedandpush_to_hubto the model which lets you upload the model and people to download and use models right away. Alternatively, you can use hf_hub_download to download checkpoints.Let me know if you're interested or need any guidance!
Kind regards,
Niels