Instructions to use shkelqim2026/EfficientNet with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use shkelqim2026/EfficientNet 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://shkelqim2026/EfficientNet") - Notebooks
- Google Colab
- Kaggle
Ctrl+K
This model has 16 files scanned as suspicious.
- ConfusionMatrix
- EfficientNet-B0
- EfficientNet-B1
- EfficientNet-B2
- EfficientNet-B3
- EfficientNet-B4
- EfficientNet-B5
- EfficientNet-B6
- EfficientNet-B7
- EfficientNet_Architecture
- Figures
- Output
- TrainingHistory
- 24.6 kB
- 17.7 kB
- 120 Bytes
- 56.2 MB xet
- 86.1 MB xet
- 100 MB xet
- 135 MB xet
- 215 MB xet
- 341 MB xet
- 485 MB xet
- 751 MB xet