Instructions to use logasja/auramask-ensemble-brooklyn with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use logasja/auramask-ensemble-brooklyn 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-brooklyn") - Notebooks
- Google Colab
- Kaggle

- Xet hash:
- b1a7ea6f34b4a850c9ea7bb9fa67cae9b36e4e9e1a9a7a2f87437f0d5dd15d90
- Size of remote file:
- 2.18 MB
- SHA256:
- 3db91632fde2acc7800d85ce5c5a0b7bb6935d27050e4101de77efa82a010398
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