Instructions to use logasja/auramask-ensemble-moon with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use logasja/auramask-ensemble-moon with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://logasja/auramask-ensemble-moon") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 37c497196cdba9739985149f567d914745e46376ce9f5bbbb7843d4ff7c08bea
- Size of remote file:
- 274 MB
- SHA256:
- c51f14653879d233cabf5867f4ddbefeb80cf20f1906d08a829c096653283504
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