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:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://febrifahmi/NoD") - Notebooks
- Google Colab
- Kaggle
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README.md
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- accuracy
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model-index:
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- name: febrifahmi/NoD (mnist_nod2_model10.keras)
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results:
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- task:
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type: image-classification
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- accuracy
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model-index:
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- name: febrifahmi/NoD (mnist_nod2_model10.keras)
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metadata:
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parameters:
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total: 116714
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trainable: 116714
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results:
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- task:
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type: image-classification
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