Image Classification
Keras
biologically-inspired
neuromorphic
dendritic-computing
green-ai
small-parameters-footprint
Eval Results (legacy)
Instructions to use febrifahmi/NoD with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use febrifahmi/NoD with Keras:
# !pip install -U keras tensorflow huggingface_hub # Keras needs TensorFlow installed to read "hf://" paths, so the tensorflow backend is selected here; # "jax" and "torch" also work for computation once TensorFlow is installed. import os os.environ["KERAS_BACKEND"] = "tensorflow" import keras model = keras.saving.load_model("hf://febrifahmi/NoD") - Notebooks
- Google Colab
- Kaggle
Download mnist_nod_model.keras from febrifahmi/NoD: direct link, hf CLI and curl.
- Browser
- Download file 223 kB
-
https://huggingface.co/febrifahmi/NoD/resolve/f34ec5dabaaf01fd78516faacfb14687ce89f2ec/mnist_nod_model.keras
- Command line
-
hf download hf://febrifahmi/NoD@f34ec5dabaaf01fd78516faacfb14687ce89f2ec/mnist_nod_model.keras
-
curl -L -o mnist_nod_model.keras https://huggingface.co/febrifahmi/NoD/resolve/f34ec5dabaaf01fd78516faacfb14687ce89f2ec/mnist_nod_model.keras
223 kB
- Xet hash:
- 074f94e1abd355df3dcafd35f720f5304f665561cbef6fc466c92074bb6a2a11
- Size of remote file:
- 223 kB
- SHA256:
- 9279860206cd3f98ff7e45f445fbcc89a8e84a6d211fbc7c0bbd83fd28614861
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