Instructions to use Vedmani/Transfer_Learning with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- TF-Keras
How to use Vedmani/Transfer_Learning with TF-Keras:
# Note: 'keras<3.x' or 'tf_keras' must be installed (legacy) # See https://github.com/keras-team/tf-keras for more details. from huggingface_hub import from_pretrained_keras model = from_pretrained_keras("Vedmani/Transfer_Learning") - Notebooks
- Google Colab
- Kaggle
Download ResNet152/saved_model.pb from Vedmani/Transfer_Learning: direct link, hf CLI and curl.
- Browser
- Download file 10.7 MB
-
https://huggingface.co/Vedmani/Transfer_Learning/resolve/main/ResNet152/saved_model.pb
- Command line
-
hf download hf://Vedmani/Transfer_Learning/ResNet152/saved_model.pb
-
curl -L -o saved_model.pb https://huggingface.co/Vedmani/Transfer_Learning/resolve/main/ResNet152/saved_model.pb
10.7 MB
- Xet hash:
- 402b7890a80904d2a2af1db39c279bf25646bd9f92e32ba522bf11a2a3fe8e13
- Size of remote file:
- 10.7 MB
- SHA256:
- 25d0dc0e34676a0dd3914638fbe85fd2f850422cff042192ce6e2045c804c693
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