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
metadata
tags:
- image-classification
metrics:
- accuracy
model-index:
- name: fruits
results:
- task:
name: Image Classification
type: image-classification
metrics:
- name: Accuracy
type: accuracy
value: 0.9896
license: unlicense
language:
- es
library_name: keras