Instructions to use liewchooichin/fake_binary with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use liewchooichin/fake_binary with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://liewchooichin/fake_binary") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ac3c48bbc4efd14264b2ae7fd04d3e9f91ef560b7a19f6490dfc2818886030b0
- Size of remote file:
- 5.1 MB
- SHA256:
- f4b59e28045a9921eb589d74030347e065f9cdbfbbfa607303d7e717f7713844
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