Instructions to use Expendadeur/agro-bio-models with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use Expendadeur/agro-bio-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://Expendadeur/agro-bio-models") - Notebooks
- Google Colab
- Kaggle
Upload online_weights.json with huggingface_hub
Browse files- online_weights.json +29 -0
online_weights.json
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{
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"model_names": [
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"EfficientNetV2M",
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"ResNet50",
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"MobileNetV3L",
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"ConvNeXtBase"
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],
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"weights_optuna": [
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0.22634092985667137,
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0.20263165013640808,
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0.3102530833043855,
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0.260774336702535
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],
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"weights_acc": [
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0.25192203328509405,
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0.24701519536903035,
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0.2512210564399421,
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0.2498417149059334
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],
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"accuracies": {
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"EfficientNetV2M": 0.9551611796982168,
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"ResNet50": 0.936556927297668,
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"MobileNetV3L": 0.9525034293552812,
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"ConvNeXtBase": 0.9472736625514403
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},
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"accuracy_ensemble_mean": 0.9613340192043895,
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"accuracy_ensemble_weighted": 0.9613340192043895,
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"accuracy_ensemble_optuna": 0.9623628257887518
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}
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