Instructions to use logasja/auramask-ensemble-mayfair with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use logasja/auramask-ensemble-mayfair 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-mayfair") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2677d5b80de31a169e1f17733b99f92ccf4cd117a1666c090f0771732f700f9c
- Size of remote file:
- 548 MB
- SHA256:
- ce6aa0d554e32df3389b337fc23e208aa7eb0cf6fcb00bec11b1a35ab024e052
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