Instructions to use harsha163/CutMix_data_augmentation_for_image_classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use harsha163/CutMix_data_augmentation_for_image_classification with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://harsha163/CutMix_data_augmentation_for_image_classification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 476e3ccf84fbac589e917565cb252f4fc8c08d62c393dcbf45458c9c5a87af14
- Size of remote file:
- 147 kB
- SHA256:
- 1d32fb83772d33f749d14671ffd2392e221a19f6c97b333285cb89f99cc62491
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