Instructions to use active-learning/mnist_classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use active-learning/mnist_classifier with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://active-learning/mnist_classifier") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a2e407e09e11460507fde37e66f5678a756a41da987d05aaee4ddfa72142aebf
- Size of remote file:
- 14 kB
- SHA256:
- 65b933d619f52778e238eefa70bb9c99031361f30809986082e06215f5d61350
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.