Instructions to use logasja/auramask-ensemble-reyes with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use logasja/auramask-ensemble-reyes 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-reyes") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0c15299800fff7a8c670e8d64f52d84f805fed77c52367163bb79a269f4fb624
- Size of remote file:
- 274 MB
- SHA256:
- d07dc6c68b727791165b3e1a96717d9f1140e1e4e06de2e8bf6591bbde28cac7
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