Instructions to use jayanthapoojary1989/rsna-pneumonia-efficientnetb0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use jayanthapoojary1989/rsna-pneumonia-efficientnetb0 with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://jayanthapoojary1989/rsna-pneumonia-efficientnetb0") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 600d5eaa8cee3cf7b00f6f979ee61afc4bafa2d8bbf4b91cde7728226162d6a4
- Size of remote file:
- 19 MB
- SHA256:
- 1df841b0e79fe2a560edb018a5a03b6dce234d4427c631b51091fef5201eab11
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