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:
- 09fa70873406d12bb7531dfc5400e35c8f48e82a5941d18af6958e29d59d2b49
- Size of remote file:
- 1.59 MB
- SHA256:
- 6d6ca6939626df61a067deef4b310f4fe1c003b49b3e9d55e036e4feaf076609
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