Instructions to use Jayanthrx/deepfake-efficientnet with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use Jayanthrx/deepfake-efficientnet with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://Jayanthrx/deepfake-efficientnet") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e4aa7c30f70719783760f6dcec107417f2c0cbe2db21f3b2f9e075e253abbf90
- Size of remote file:
- 37.4 MB
- SHA256:
- 04ed9179bd0d4980fdf3cfaede5b1357bafa881d1c426d93fbbaf34fbb976709
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