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
File size: 678 Bytes
bd5335b | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 | {
"model_names": [
"EfficientNetV2M",
"ResNet50",
"MobileNetV3L",
"ConvNeXtBase"
],
"weights_optuna": [
0.22634092985667137,
0.20263165013640808,
0.3102530833043855,
0.260774336702535
],
"weights_acc": [
0.25192203328509405,
0.24701519536903035,
0.2512210564399421,
0.2498417149059334
],
"accuracies": {
"EfficientNetV2M": 0.9551611796982168,
"ResNet50": 0.936556927297668,
"MobileNetV3L": 0.9525034293552812,
"ConvNeXtBase": 0.9472736625514403
},
"accuracy_ensemble_mean": 0.9613340192043895,
"accuracy_ensemble_weighted": 0.9613340192043895,
"accuracy_ensemble_optuna": 0.9623628257887518
} |