Instructions to use logasja/auramask-ensemble-charmes with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use logasja/auramask-ensemble-charmes 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-charmes") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f68a5b23f7cd6ed7c3a51987fa2366571d9b2b5efab78760c5e52c794b4112f9
- Size of remote file:
- 274 MB
- SHA256:
- 92d5c1dd10d5ac1c76eed6ba42774bacf50c9392cb29b5d44b1515452a5ae449
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