Instructions to use Juna190825/github_jeffprosise_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use Juna190825/github_jeffprosise_model with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://Juna190825/github_jeffprosise_model") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f2673dda913fcce4e91a05d6781ee38847cd9ef6b4fc9d3b7da75acb72479be0
- Size of remote file:
- 190 MB
- SHA256:
- 03ef222464d5ff2db8b3c4f2fab339e7b6907665d68c503679cf8acf118ac811
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.