Hi @WahabF 🤗
Niels here from the open-source team at Hugging Face. I discovered your work on Arxiv and your project page: https://vision-cair.github.io/iMotion-LLM/. I noticed you're planning to release the code, pre-trained model (iMotion-LLM), and datasets (InstructWaymo, Open-Vocabulary InstructNuPlan) soon.
The Hugging Face paper page (https://huggingface.co/papers/2406.06211) lets people discuss your paper and find related artifacts (your models, datasets, or demos). 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 iMotion-LLM checkpoints and the InstructWaymo and Open-Vocabulary InstructNuPlan datasets available on the 🤗 Hub once they are ready, 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
See here for a guide: https://huggingface.co/docs/hub/models-uploading.
In this case, we could leverage the PyTorchModelHubMixin class which adds from_pretrained and push_to_hub to any custom nn.Module. Alternatively, one can leverages 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 also work. We can then also link the checkpoints to the paper page. For iMotion-LLM, the pipeline tag would likely be "robotics" for trajectory generation.
Uploading dataset
Would be awesome to make the datasets available on 🤗 , 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. For InstructWaymo and Open-Vocabulary InstructNuPlan, the task category would be "robotics".
Let me know if you're interested/need any help regarding this, once your artifacts are ready for release!
Cheers,
Niels
ML Engineer @ HF 🤗
Hi @WahabF 🤗
Niels here from the open-source team at Hugging Face. I discovered your work on Arxiv and your project page: https://vision-cair.github.io/iMotion-LLM/. I noticed you're planning to release the code, pre-trained model (
iMotion-LLM), and datasets (InstructWaymo,Open-Vocabulary InstructNuPlan) soon.The Hugging Face paper page (https://huggingface.co/papers/2406.06211) lets people discuss your paper and find related artifacts (your models, datasets, or demos). 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
iMotion-LLMcheckpoints and theInstructWaymoandOpen-Vocabulary InstructNuPlandatasets available on the 🤗 Hub once they are ready, 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
See here for a guide: https://huggingface.co/docs/hub/models-uploading.
In this case, we could leverage the PyTorchModelHubMixin class which adds
from_pretrainedandpush_to_hubto any customnn.Module. Alternatively, one can leverages 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 also work. We can then also link the checkpoints to the paper page. For
iMotion-LLM, the pipeline tag would likely be "robotics" for trajectory generation.Uploading dataset
Would be awesome to make the 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. For
InstructWaymoandOpen-Vocabulary InstructNuPlan, the task category would be "robotics".Let me know if you're interested/need any help regarding this, once your artifacts are ready for release!
Cheers,
Niels
ML Engineer @ HF 🤗