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Niels here from the open-source team at Hugging Face. I discovered your work through ECCV (congrats) and indexed your paper here: https://huggingface.co/papers/2311.11241. The paper page lets people discuss the paper, and discover its artifacts (such as models, dataset, a demo in the form of a 🤗 Space).
It'd be great to make the checkpoints and dataset available on the 🤗 hub, rather than Google Drive, to improve their discoverability/visibility. We can add tags so that people find them when filtering https://huggingface.co/models and https://huggingface.co/datasets.
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.
Uploading dataset
Would be awesome to make the dataset available on 🤗 , so that people can do:
---- Replied Message ----
| From | ***@***.***> |
| Date | 09/30/2024 10:01 |
| To | ***@***.***> |
| Cc | ***@***.***>***@***.***> |
| Subject | [lartpang/OVCamo] Release artifacts (model, dataset) on Hugging Face (Issue #2) |
Hi @floatingstarZ,
Niels here from the open-source team at Hugging Face. I discovered your work through ECCV (congrats) and indexed your paper here: https://huggingface.co/papers/2311.11241. The paper page lets people discuss the paper, and discover its artifacts (such as models, dataset, a demo in the form of a 🤗 Space).
It'd be great to make the checkpoints and dataset available on the 🤗 hub, rather than Google Drive, to improve their discoverability/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.
Uploading dataset
Would be awesome to make the dataset available on 🤗 , so that people can do:
fromdatasetsimportload_datasetdataset=load_dataset("your-hf-org/your-dataset")
See here for a guide: https://huggingface.co/docs/datasets/image_dataset
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/need any help regarding this!
Cheers,
Niels
ML Engineer @ HF 🤗
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You are receiving this because you were mentioned.Message ID: ***@***.***>
Hi @floatingstarZ,
Niels here from the open-source team at Hugging Face. I discovered your work through ECCV (congrats) and indexed your paper here: https://huggingface.co/papers/2311.11241. The paper page lets people discuss the paper, and discover its artifacts (such as models, dataset, a demo in the form of a 🤗 Space).
It'd be great to make the checkpoints and dataset available on the 🤗 hub, rather than Google Drive, to improve their discoverability/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
andpush_to_hub
to 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.
Uploading dataset
Would be awesome to make the dataset available on 🤗 , so that people can do:
See here for a guide: https://huggingface.co/docs/datasets/image_dataset
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/need any help regarding this!
Cheers,
Niels
ML Engineer @ HF 🤗
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