Instructions to use logasja/auramask-ensemble-ginza with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use logasja/auramask-ensemble-ginza 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-ginza") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 30e6c976bf807028b06f7086c833ea7f673443d161c5dd5167645b82deba0d5c
- Size of remote file:
- 274 MB
- SHA256:
- 7ca3debcd841ed58137a2d8c0a1121b7fbd30937ef44e5d6cd4d31c647f9b30b
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