opendilab / opendilab/LightZero

Release PriorZero checkpoints on Hugging Face

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Description

Hi @opendilab 🤗

I'm Niels and work as part of 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 for instance), you can also claim the paper as yours which will show up on your public profile at HF, and add your Github and project page URLs.

I saw that you are planning to release the code for PriorZero in the LightZero repository. We are big fans of the OpenDILab projects! Would you like to host the model checkpoints you've pre-trained (such as the world models or the fine-tuned LLM adapters for Jericho and BabyAI) on https://huggingface.co/models?

Hosting on Hugging Face will give you more visibility and enable better discoverability. We can add tags in the model cards so that people find the models easier, link it to the paper page, etc.

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, or simply use hf_hub_download to let people download and use the weights directly.

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 model on Spaces, we can provide you a ZeroGPU grant, which gives you A100 GPUs for free.

Let me know if you're interested/need any guidance :)

Kind regards,

Niels

Contributor guide

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First steps

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  2. Comment on the issue to say you are picking it up — it saves two people doing the same work.
  3. Fork the repository and make your change on a branch.
  4. Open a pull request that references the issue number.

Research direction

The issue names no repository files, tests, or entry points. Start with the Hugging Face model-uploading guide and identify the PriorZero world models and fine-tuned LLM adapters for Jericho and BabyAI; done means the selected checkpoints are hosted with model cards and linked to the paper page.

Written by the indexing model from the issue text.

Assessment

Tech stack
python, pytorch
Domain
machine-learning, release
Issue type
Feature
Difficulty
4/5
Estimated time
3-5 days
Activity status
Quiet
Clarity
Needs clarification
Newbie friendliness
35/100

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