Instructions to use DeekshaShetty/iti107assignment2-model2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- TF-Keras
How to use DeekshaShetty/iti107assignment2-model2 with TF-Keras:
# Note: 'keras<3.x' or 'tf_keras' must be installed (legacy), and from_pretrained_keras was removed in huggingface_hub 1.0. # See https://github.com/keras-team/tf-keras for more details. # !pip install "huggingface_hub<1.0" tf_keras from huggingface_hub import from_pretrained_keras model = from_pretrained_keras("DeekshaShetty/iti107assignment2-model2") - Notebooks
- Google Colab
- Kaggle
Download saved_model/saved_model.pb from DeekshaShetty/iti107assignment2-model2: direct link, hf CLI and curl.
- Browser
- Download file 9.24 MB
-
https://huggingface.co/DeekshaShetty/iti107assignment2-model2/resolve/main/saved_model/saved_model.pb
- Command line
-
hf download hf://DeekshaShetty/iti107assignment2-model2/saved_model/saved_model.pb
-
curl -L -o saved_model.pb https://huggingface.co/DeekshaShetty/iti107assignment2-model2/resolve/main/saved_model/saved_model.pb
9.24 MB
- Xet hash:
- 8e146b8b3fe0d25be11668c347a68a6dd0b8bf493cba386c2a07acdc35de27d0
- Size of remote file:
- 9.24 MB
- SHA256:
- 5e1a50c71f524048b86d81d36629417f0dd4254eecea91b351409b72e59af92a
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