Instructions to use ZenithsArch/Avalanche_Classification_Weights with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use ZenithsArch/Avalanche_Classification_Weights 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://ZenithsArch/Avalanche_Classification_Weights") - Notebooks
- Google Colab
- Kaggle
Upload model: last_EfficientNetV2S_vr20_augstandard_seed42
Browse files
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models/B_Sobel_EfficientNetV2S.keras filter=lfs diff=lfs merge=lfs -text
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models/B_Sobel_EfficientNetV2S_Phase2.keras filter=lfs diff=lfs merge=lfs -text
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models/last_EfficientNetV2S_vr20_augcutmix_seed42.keras filter=lfs diff=lfs merge=lfs -text
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models/B_Sobel_EfficientNetV2S_Phase2.keras filter=lfs diff=lfs merge=lfs -text
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models/last_EfficientNetV2S_vr20_augcutmix_seed42.keras filter=lfs diff=lfs merge=lfs -text
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models/last_EfficientNetV2S_vr20_augstandard_seed42.keras filter=lfs diff=lfs merge=lfs -text
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models/last_EfficientNetV2S_vr20_augstandard_seed42.keras
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size 137907541
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