Instructions to use Ritz-ai/reciclaje-efficientnetb0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use Ritz-ai/reciclaje-efficientnetb0 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://Ritz-ai/reciclaje-efficientnetb0") - Notebooks
- Google Colab
- Kaggle
Commit History
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Add TFLite model for mobile
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Initial model upload: EfficientNetB0 trained for recycling classification
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Create README.md
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2025-10-19 19:39:55Z - upload final_efficientnet.keras
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2025-10-19 19:39:55Z - upload best_efficientnet.keras
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Best model (early stopped, fine-tuned EfficientNetB0)
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Initial model upload: EfficientNetB0 trained for recycling classification
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initial commit
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