Instructions to use logasja/auramask-ensemble-hudson with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use logasja/auramask-ensemble-hudson 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-hudson") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7b7eb521528d65e4bd38f2193be44e8c2d746a7ab2586996486063adb78d41e7
- Size of remote file:
- 548 MB
- SHA256:
- 59eba6a1ab7a88f512d3fcbbce3bd758a7ff2d8c44b8e79d4d78cd81c78b67a2
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