Instructions to use logasja/auramask-ensemble-toaster with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use logasja/auramask-ensemble-toaster 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-toaster") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 742527ac379a70fb2219e6f02e98b9b6dfd48f4d81530c4f19e5737ecd79cf7c
- Size of remote file:
- 274 MB
- SHA256:
- 2a896aa02415deb6f199ac60dd685a7445dc2eda47c961264b7b8b938182f266
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