Either run in your terminal: | |
huggingface-cli login | |
or from a notebook: | |
from huggingface_hub import notebook_login | |
notebook_login() | |
You can then push to your own namespace (or an organization you are a member of) like this: | |
py | |
resnet50d.push_to_hub("custom-resnet50d") | |
On top of the modeling weights and the configuration in json format, this also copied the modeling and | |
configuration .py files in the folder custom-resnet50d and uploaded the result to the Hub. |