Instructions to use MoyAI/password-security with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use MoyAI/password-security with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://MoyAI/password-security") - Notebooks
- Google Colab
- Kaggle
Update README.md
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README.md
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The model was trained on 4,2MiB (`200 000` lines) of .csv data for 2 epochs on Adam with learning rate 0.00001, batch size 4 and mse loss.
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The model embeds every input character with the ord() builtin python function. The model has `128 969` dense layer parameters.
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## Evaluation
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**loss** - 0.0025
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**accuracy** - 0.9972
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The
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**loss** - 0.0023
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**accuracy** - 0.9972
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## Model usage
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The model was trained on 4,2MiB (`200 000` lines) of .csv data for 2 epochs on Adam with learning rate 0.00001, batch size 4 and mse loss.
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The model embeds every input character with the ord() builtin python function. The model has `128 969` dense layer parameters.
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## Evaluation
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During training the model had:
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**loss** - 0.0025
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**accuracy** - 0.9972
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The test metrics are:
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**loss** - 0.0023
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**accuracy** - 0.9972
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## Model usage
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