Hello,
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 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.
It'd be great to make the checkpoints and datasets available on the 🤗 hub to improve their discoverability and visibility. We can add tags so that people find them when filtering https://huggingface.co/models and https://huggingface.co/datasets.
Uploading models
I see you have released the code for training the Context Augmentation Model (CAM). Would you like to host the pre-trained CAM checkpoints on https://huggingface.co/models? Hosting on Hugging Face will give you more visibility and enable better discoverability.
See here for a guide: https://huggingface.co/docs/hub/models-uploading.
In this case, since you use LLaMA-Factory and Transformers, you can use the built-in push_to_hub methods. Alternatively, one can leverage the hf_hub_download one-liner to download a checkpoint from the hub.
Uploading dataset
I see you're currently hosting the SFT training data and task trajectories in the GitHub repository. Would be awesome to make these CLEAR datasets available on 🤗 , so that people can do:
from datasets import load_dataset
dataset = load_dataset("your-hf-org-or-username/clear-appworld-sft")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 🤗
Hello,
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 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.
It'd be great to make the checkpoints and datasets available on the 🤗 hub to improve their discoverability and visibility. We can add tags so that people find them when filtering https://huggingface.co/models and https://huggingface.co/datasets.
Uploading models
I see you have released the code for training the Context Augmentation Model (CAM). Would you like to host the pre-trained CAM checkpoints on https://huggingface.co/models? Hosting on Hugging Face will give you more visibility and enable better discoverability.
See here for a guide: https://huggingface.co/docs/hub/models-uploading.
In this case, since you use LLaMA-Factory and Transformers, you can use the built-in
push_to_hubmethods. Alternatively, one can leverage the hf_hub_download one-liner to download a checkpoint from the hub.Uploading dataset
I see you're currently hosting the SFT training data and task trajectories in the GitHub repository. Would be awesome to make these CLEAR datasets available on 🤗 , 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 🤗