Instructions to use DataScienceProject/CNN with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use DataScienceProject/CNN with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://DataScienceProject/CNN") - Notebooks
- Google Colab
- Kaggle
Create requirements.txt
Browse files- requirements.txt +7 -0
requirements.txt
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tensorflow: The deep learning framework used for building and training the model.
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numpy: For numerical operations and handling arrays.
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pandas: For data manipulation and analysis.
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scikit-learn: For machine learning utilities, including cross-validation and metrics.
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opencv-python: For image processing tasks.
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matplotlib: For plotting and visualizing training results.
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h5py: For saving and loading model weights in HDF5 format.
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