Instructions to use adarshcod30/openforensics-ensemble with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use adarshcod30/openforensics-ensemble with Keras:
# !pip install -U keras tensorflow huggingface_hub # Keras needs TensorFlow installed to read "hf://" paths, so the tensorflow backend is selected here; # "jax" and "torch" also work for computation once TensorFlow is installed. import os os.environ["KERAS_BACKEND"] = "tensorflow" import keras model = keras.saving.load_model("hf://adarshcod30/openforensics-ensemble") - Notebooks
- Google Colab
- Kaggle
Commit History
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State the scope limit: face swaps, not AI-generated images
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Bundle training curves, logs and leakage report for the dashboard
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v2: three-backbone ensemble with corruption-matched augmentation
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v1: two-backbone ensemble (ResNet50+VGG16), calibrated, TTA-evaluated
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initial commit
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