Instructions to use nico9ga/fruits-Classification-Model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use nico9ga/fruits-Classification-Model with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://nico9ga/fruits-Classification-Model") - Notebooks
- Google Colab
- Kaggle
| { | |
| "num_classes": 20, | |
| "class_names": ["Banano", "Durazno", "Fresa", "Guanabana", "Guayaba", "Kiwi", "Limon", "Lulo", "Mandarina", "Mango", "Manzana", "Manzana Verde", "Melon", "Mora", "Naranja", "Papaya", "Pera", "Piña", "Sandia", "Tomate de Arbol"], | |
| "input_size": [100, 100, 3], | |
| "model_type": "ResNet50V2" | |
| } |