Instructions to use Ravindra001/conv_bn with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use Ravindra001/conv_bn with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://Ravindra001/conv_bn") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 84bebe02cd5f511683aabed32138fae34f18f9ea555cea4d17eba76a4a5fc536
- Size of remote file:
- 30.8 kB
- SHA256:
- 3f7cc635ff802b9c9eb9d99c02a68194d49785c94e345c5b808340d2c9d52189
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.