Closed NielsRogge closed 2 months ago
Thanks for the instruction! We will integrate to HF ASAP.
Awesome!! Also opened a PR to link it to the paper page: https://huggingface.co/Study-is-happy/neuflow-v2/discussions/1.
We will work on adding a dedicated "optical-flow-estimation" tag so that people can easier discover models like yours (cc @merveenoyan).
We also hope researchers can leverage the tools from huggingface_hub for their future works.
Cheers :)
Niels
Awesome!! Also opened a PR to link it to the paper page: https://huggingface.co/Study-is-happy/neuflow-v2/discussions/1.
We will work on adding a dedicated "optical-flow-estimation" tag so that people can easier discover models like yours (cc @merveenoyan).
We also hope researchers can leverage the tools from huggingface_hub for their future works.
Cheers :)
Niels
Thanks Niels! We have merged the PR on HuggingFace and looking forward to the "optical-flow-estimation" tag!
Hi,
Thanks for this nice work! I wrote a quick PoC to showcase that you can easily have integration with the 🤗 hub so that you can automatically load the model using
from_pretrained
(and push it usingpush_to_hub
), track download numbers for your models (similar to models in the Transformers library), and have nice model cards on a per-model basis, and perhaps most importantly, leveragesafetensors
for the weights in favor of pickle.It leverages the PyTorchModelHubMixin class which allows to inherits these methods.
Usage is as follows:
This means people don't need to manually download a checkpoint first in their local environment, it just loads automatically from the hub, and they can discover it when filtering https://huggingface.co/models.
Would you be interested in this integration?
Kind regards,
Niels
Note
Please don't merge this PR before pushing the model to the hub :)