Instructions to use logasja/auramask-ensemble-xpro2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use logasja/auramask-ensemble-xpro2 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-xpro2") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5880f6f2314c1cc08795a950e1eb55c5b5b072c545ec7ef3ed538d141377d1f1
- Size of remote file:
- 548 MB
- SHA256:
- dd664b52004677ee4ac3cdc9423494832a79f59c5f5c7bc363ea2edf411f5417
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