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:
- e8e46d8e06ebc552e8372803f704cd6d1c32fc50dee3432ccd46ad87c1a42eb7
- Size of remote file:
- 34.2 kB
- SHA256:
- c559657cbfe1bb6f9ba369d6595fb10d74673149f9534d9fc7939dad6a637e6c
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