Instructions to use logasja/auramask-ensemble-hefe with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use logasja/auramask-ensemble-hefe 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-hefe") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e7dfc6972fe8aaf6aa7c0bb5674ba3f95342f439b35c5c4b94158d40d595f440
- Size of remote file:
- 274 MB
- SHA256:
- d934b77fff0fce0872ec79528ba91b3171cb75dd901aeda67ea35a01233d42c6
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