Instructions to use danielle2035/intel-classifier-models with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use danielle2035/intel-classifier-models with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://danielle2035/intel-classifier-models") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b556aacc4890d41c1f29e0f4101e59bbd1038c83fc0564d93cf83d10e35af9b2
- Size of remote file:
- 5.16 MB
- SHA256:
- 1b57e8ec14d2c7fa3f168d95fdf02e98d6a5626ae5648975d98d0cb265aed8a9
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.