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OKTAYBBS
/
DataScientst-models

Tabular Classification
Keras
Scikit-learn
English
tensorflow
random-forest
cnn
clustering
nlp
computer-vision
recommendation-system
time-series
streamlit
Model card Files Files and versions
xet
Community

Instructions to use OKTAYBBS/DataScientst-models with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Keras

    How to use OKTAYBBS/DataScientst-models with Keras:

    # Available backend options are: "jax", "torch", "tensorflow".
    import os
    os.environ["KERAS_BACKEND"] = "jax"
    
    import keras
    
    model = keras.saving.load_model("hf://OKTAYBBS/DataScientst-models")
    
  • Scikit-learn

    How to use OKTAYBBS/DataScientst-models with Scikit-learn:

    from huggingface_hub import hf_hub_download
    import joblib
    model = joblib.load(
    	hf_hub_download("OKTAYBBS/DataScientst-models", "sklearn_model.joblib")
    )
    # only load pickle files from sources you trust
    # read more about it here https://skops.readthedocs.io/en/stable/persistence.html
  • Notebooks
  • Google Colab
  • Kaggle
DataScientst-models / metrics
56 kB
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  • 1 contributor
History: 3 commits

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  • metrics.json
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  • metrics_summary.csv
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  • metrics_summary.png
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