Instructions to use logasja/auramask-ensemble-willow with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use logasja/auramask-ensemble-willow 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-willow") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7d28b253953f200ef7137e95dac2e5065693049a573c7c91aaca22cc949a912a
- Size of remote file:
- 274 MB
- SHA256:
- 26f4a7c9d8cb0077395e7319b5f16e035f5d4ba805cbb00b9237365bef14660c
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