Instructions to use pratikdoshi/spam-classification-fully-connected with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use pratikdoshi/spam-classification-fully-connected with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://pratikdoshi/spam-classification-fully-connected") - Notebooks
- Google Colab
- Kaggle
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library_name: keras
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## Model description
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| momentum | 0.0 |
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| epsilon | 1e-07 |
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| centered | False |
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| training_precision | float32 |
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library_name: keras
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language:
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- en
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metrics:
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- accuracy
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pipeline_tag: text-classification
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---
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## Model description
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| momentum | 0.0 |
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| epsilon | 1e-07 |
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| centered | False |
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| training_precision | float32 |
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