Instructions to use logasja/auramask-ensemble-juno with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use logasja/auramask-ensemble-juno 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-juno") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4c12d73b24f57c6f0423663e2ac3954ed9470823e365783974f1c3ebe9919cbd
- Size of remote file:
- 274 MB
- SHA256:
- c384d44b191d2a6e8e0936e2075a8cd0e28310c522008d6a9121c03855b37d74
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