Instructions to use logasja/auramask-ensemble-poprocket with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use logasja/auramask-ensemble-poprocket 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-poprocket") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 55802061494482fbc10b372b8ceea08d9d46ad7c53e1b66e1dadea2b49d8f7ed
- Size of remote file:
- 274 MB
- SHA256:
- afdfe9fd4c4aced941130f0cf8529967cf3781c6179c52ce01373285b0fbac52
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