Instructions to use edogarci/cnn_cell_binary_class with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use edogarci/cnn_cell_binary_class with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://edogarci/cnn_cell_binary_class") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 871e48fb36b1035d296cefc5fdd3487a7be3752df3c0b67baa414c6a201df4e9
- Size of remote file:
- 20 MB
- SHA256:
- 0ca7bf1af19766cedba7b60b0cd3b0532f896794b791ae3ffc0f09942e47a0a7
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