Instructions to use logasja/auramask-ensemble-xpro2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use logasja/auramask-ensemble-xpro2 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-xpro2") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e16036b191c254c0e11c8ee4f1e3f4c9be9ab3760adbcb059ab55e22ce36d302
- Size of remote file:
- 274 MB
- SHA256:
- 2b1bae5e67c0146194d2b6559dd7f89d56236efcea04607fd8b0eb738cb2b197
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