Instructions to use merve/hyperparam_table with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use merve/hyperparam_table with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://merve/hyperparam_table") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ee4c532a3069089c7a21bc4fc819f1574261096ed561bede07eccee41f3bf2fe
- Size of remote file:
- 391 Bytes
- SHA256:
- 9d30c82a262742cd1be3419ce9c41fb8a41dee0390ec5eed7e9d8f7d1dae6ad1
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