Instructions to use emergentai/cancer-efficientnetb7-undersampling with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use emergentai/cancer-efficientnetb7-undersampling with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://emergentai/cancer-efficientnetb7-undersampling") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5761071233cb49b5652a8980b2689cd535b9d75e7faeb6d6f0ace2fa396f7f53
- Size of remote file:
- 321 MB
- SHA256:
- 7b9cdcb809cd04c39a84c1c982d4ee8200cb600bf72605ab7c900ac177e38d03
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