Hi @tianlef 🤗
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/2502.11034.
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.
Would you like to host the models you've pre-trained (such as the Llama-2 7B, Mixtral 8x1B, and ERNIE 10B-A1.4B checkpoints trained with AdaGC) on https://huggingface.co/models?
Hosting on Hugging Face will give your work more visibility and enable better discoverability. We can add tags in the model cards so that people find the models easier, link them to the paper page, etc.
If you're down, leaving a guide here. If it's a custom PyTorch or PaddlePaddle model, you can use the PyTorchModelHubMixin (or equivalent integration) to allow people to download and use the models right away. Alternatively, researchers can use hf_hub_download to pull the files.
After uploaded, we can also link the models to the paper page (read here) so people can discover your work.
You can also build a demo for your models on Spaces; we can provide you a ZeroGPU grant, which gives you free GPU-backed compute for eligible demo Spaces.
Let me know if you're interested/need any guidance :)
Kind regards,
Niels
Hi @tianlef 🤗
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/2502.11034.
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.
Would you like to host the models you've pre-trained (such as the Llama-2 7B, Mixtral 8x1B, and ERNIE 10B-A1.4B checkpoints trained with AdaGC) on https://huggingface.co/models?
Hosting on Hugging Face will give your work more visibility and enable better discoverability. We can add tags in the model cards so that people find the models easier, link them to the paper page, etc.
If you're down, leaving a guide here. If it's a custom PyTorch or PaddlePaddle model, you can use the PyTorchModelHubMixin (or equivalent integration) to allow people to download and use the models right away. Alternatively, researchers can use hf_hub_download to pull the files.
After uploaded, we can also link the models to the paper page (read here) so people can discover your work.
You can also build a demo for your models on Spaces; we can provide you a ZeroGPU grant, which gives you free GPU-backed compute for eligible demo Spaces.
Let me know if you're interested/need any guidance :)
Kind regards,
Niels