Instructions to use asigalov61/B-CLassi with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use asigalov61/B-CLassi with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://asigalov61/B-CLassi") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 642d31bfdd6f2c411924cb805aaa6619b52d2fddb9413a4996dd022dc01ec315
- Size of remote file:
- 47.1 MB
- SHA256:
- c90f4e951339227170584a3497ab9fe472538cebb30b1d6a8fd0033d2e2b72df
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