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:
- 28d95d626653eae28f2621df85ea23a96299530996ef95a054cf3890fa4dca4f
- Size of remote file:
- 3.37 kB
- SHA256:
- 6321488039efbc37c3dd4e6a42901f5b37144de8d971b110665484b86e114d6c
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.