Instructions to use logasja/auramask-ensemble-mayfair with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use logasja/auramask-ensemble-mayfair 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-mayfair") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 60089ad0e5d4daf6aa484ef2dd4f3317a91dafae48ef75c3e78880bdcfffad3a
- Size of remote file:
- 274 MB
- SHA256:
- 3823b84b77b4f08fca5e0b8dcf52f8fb24de7ca3800f3a513e2eac3c438c8c31
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