Hi @yqingFU1007 🤗
Niels here from the open-source team at Hugging Face. I discovered your work on Arxiv and was wondering whether you would like to submit it to hf.co/papers to improve its discoverability. If you are one of the authors, you can submit it at https://huggingface.co/papers/submit.
The paper page (https://huggingface.co/papers/2604.24515) lets people discuss about your paper and lets them find artifacts about it (your models, datasets or demo for instance), you can also claim the paper as yours which will show up on your public profile at HF, and add Github and project page URLs.
I saw on your Github repository that the code and dataset for SEARCH-R are being prepared for release. It'd be great to make the fine-tuned Llama 3.1 checkpoints and your reasoning dataset available on the 🤗 hub to improve their discoverability and visibility. We can add metadata tags so that people find them easily when filtering https://huggingface.co/models and https://huggingface.co/datasets.
Uploading models
See here for a guide: https://huggingface.co/docs/hub/models-uploading.
In this case, since you are fine-tuning a Llama 3.1-8B model, we could leverage the PyTorchModelHubMixin class which adds from_pretrained and push_to_hub to any custom nn.Module. Alternatively, one can leverage 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 work correctly. We can then also link the checkpoints directly to the paper page.
Uploading dataset
Would be awesome to make the dataset you constructed for training the navigator available on 🤗 as well, so that people can do:
from datasets import load_dataset
dataset = load_dataset("your-hf-org-or-username/your-dataset")See here for a guide: https://huggingface.co/docs/datasets/loading.
Besides that, there's the dataset viewer which allows people to quickly explore the first few rows of the data in the browser.
Let me know if you're interested or need any help regarding this!
Cheers,
Niels
ML Engineer @ HF 🤗
Hi @yqingFU1007 🤗
Niels here from the open-source team at Hugging Face. I discovered your work on Arxiv and was wondering whether you would like to submit it to hf.co/papers to improve its discoverability. If you are one of the authors, you can submit it at https://huggingface.co/papers/submit.
The paper page (https://huggingface.co/papers/2604.24515) lets people discuss about your paper and lets them find artifacts about it (your models, datasets or demo for instance), you can also claim the paper as yours which will show up on your public profile at HF, and add Github and project page URLs.
I saw on your Github repository that the code and dataset for SEARCH-R are being prepared for release. It'd be great to make the fine-tuned Llama 3.1 checkpoints and your reasoning dataset available on the 🤗 hub to improve their discoverability and visibility. We can add metadata tags so that people find them easily when filtering https://huggingface.co/models and https://huggingface.co/datasets.
Uploading models
See here for a guide: https://huggingface.co/docs/hub/models-uploading.
In this case, since you are fine-tuning a Llama 3.1-8B model, we could leverage the PyTorchModelHubMixin class which adds
from_pretrainedandpush_to_hubto any customnn.Module. Alternatively, one can leverage 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 work correctly. We can then also link the checkpoints directly to the paper page.
Uploading dataset
Would be awesome to make the dataset you constructed for training the navigator available on 🤗 as well, so that people can do:
See here for a guide: https://huggingface.co/docs/datasets/loading.
Besides that, there's the dataset viewer which allows people to quickly explore the first few rows of the data in the browser.
Let me know if you're interested or need any help regarding this!
Cheers,
Niels
ML Engineer @ HF 🤗